Yield Optimization with Model Based DFM

Model-Based Design Analysis and Yield Optimization

IEEE Transactions on Semiconductor Manufacturing ◽

10.1109/tsm.2006.883589 ◽

2006 ◽

Vol 19 (4) ◽

pp. 475-486 ◽

Cited By ~ 10

Author(s):

Tobias Pfingsten ◽

Daniel J. L. Herrmann ◽

Carl Edward Rasmussen

Keyword(s):

Design Analysis ◽

Yield Optimization ◽

Model Based

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Yield optimization of cotton fiber, using a regression model based on the conditions of entry and process at the stage of ginning

Ingeniería y Desarrollo ◽

10.14482/inde.32.1.4723 ◽

2014 ◽

Vol 32 (1) ◽

pp. 26-40

Author(s):

Álvaro Gómez Osorio ◽

Marco E. Sanjuán Mejía

Keyword(s):

Regression Model ◽

Cotton Fiber ◽

Yield Optimization ◽

Model Based

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A SVM Surrogate Model-Based Method for Parametric Yield Optimization

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems ◽

10.1109/tcad.2015.2501307 ◽

2016 ◽

Vol 35 (7) ◽

pp. 1224-1228 ◽

Cited By ~ 2

Author(s):

Angelo Ciccazzo ◽

Gianni Di Pillo ◽

Vittorio Latorre

Keyword(s):

Surrogate Model ◽

Yield Optimization ◽

Model Based ◽

Parametric Yield

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Enhance convergence of MFQ-model based yield optimization [MMICs]

Proceedings of 1997 Asia-Pacific Microwave Conference ◽

10.1109/apmc.1997.654681 ◽

2002 ◽

Cited By ~ 1

Author(s):

Zhao Desong ◽

Gao Baoxin ◽

Zhao Zhengping

Keyword(s):

Yield Optimization ◽

Model Based

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

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.

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

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

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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