scholarly journals T-Fuzz: Model-Based Fuzzing for Robustness Testing of Telecommunication Protocols

2014 ◽  
Author(s):  
William Johansson ◽  
Martin Svensson ◽  
Ulf E. Larson ◽  
Magnus Almgren ◽  
Vincenzo Gulisano
Keyword(s):  
Robustness Testing ◽  
Model Based ◽  
Telecommunication Protocols

Accelerated model-based robustness testing of state machine implementations

2013 ◽  
Vol 13 (3) ◽  
pp. 50-67 ◽  
Author(s):  
Patrick Heckeler ◽  
Hanno Eichelberger ◽  
Thomas Kropf ◽  
Jürgen Ruf ◽  
Stefan Huster ◽  
...  
Keyword(s):  
State Machine ◽  
Robustness Testing ◽  
Model Based

scholarly journals Model-Based Robustness Testing in Event-B Using Mutation

2015 ◽  
pp. 132-147 ◽  
Author(s):  
Aymerick Savary ◽  
Marc Frappier ◽  
Michael Leuschel ◽  
Jean-Louis Lanet
Keyword(s):  
Robustness Testing ◽  
Model Based

scholarly journals Model-based robustness testing for avionics-embedded software

2013 ◽  
Vol 26 (3) ◽  
pp. 730-740 ◽  
Author(s):  
Shunkun Yang ◽  
Bin Liu ◽  
Shihai Wang ◽  
Minyan Lu
Keyword(s):  
Embedded Software ◽  
Robustness Testing ◽  
Model Based

scholarly journals A Model-Based Approach for Robustness Testing

2005 ◽  
pp. 333-348 ◽  
Author(s):  
Jean-Claude Fernandez ◽  
Laurent Mounier ◽  
Cyril Pachon
Keyword(s):  
Robustness Testing ◽  
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

Model-Based Software Testing and Analysis with C#

2007 ◽  
Author(s):  
Jonathan Jacky ◽  
Margus Veanes ◽  
Colin Campbell ◽  
Wolfram Schulte
Keyword(s):  
Software Testing ◽  
Model Based
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