Toward a Model-Based Approach to Dynamic Adaptation of Composite Services

2008 ◽  
Author(s):  
Wei Song ◽  
Xiaoxing Ma ◽  
Wanchun Dou ◽  
Jian Lü
Keyword(s):  
Dynamic Adaptation ◽  
Model Based ◽  
Composite Services

Robust dynamic adaptation of the Smagorinsky model based on a sub-grid activity sensor

2021 ◽  
Vol 33 (1) ◽  
pp. 015117
Author(s):  
J. Hasslberger ◽  
L. Engelmann ◽  
A. Kempf ◽  
M. Klein
Keyword(s):  
Dynamic Adaptation ◽  
Smagorinsky Model ◽  
Model Based

scholarly journals Workload Model Based Dynamic Adaptation of Social Internet of Vehicles

Sensors ◽  
2015 ◽  
Vol 15 (9) ◽  
pp. 23262-23285 ◽  
Author(s):  
Kazi Alam ◽  
Mukesh Saini ◽  
Abdulmotaleb Saddik
Keyword(s):  
Dynamic Adaptation ◽  
Internet Of Vehicles ◽  
Model Based

scholarly journals Security-driven model-based dynamic adaptation

2010 ◽  
Author(s):  
Brice Morin ◽  
Tejeddine Mouelhi ◽  
Franck Fleurey ◽  
Yves Le Traon ◽  
Olivier Barais ◽  
...  
Keyword(s):  
Dynamic Adaptation ◽  
Model Based

A New Model for Web Service Composition

2011 ◽  
Vol 219-220 ◽  
pp. 638-642
Author(s):  
Long Hao
Keyword(s):  
Web Service ◽  
Service Composition ◽  
Optimization Methods ◽  
Web Service Composition ◽  
New Model ◽  
Model Based ◽  
Multiple Input ◽  
Composite Services ◽  
Individual Service

To support automated Web service composition, it is compelling to provide a template, or model that dictates the ways in which services can be composed. In this paper, a novel composition model based on the relative vector is proposed, where individual services, composite services, and user objectives are described with the relative vectors, through a series of operators defined on the relative vector, available composite services can be found, and how much they meet user objectives can be evaluated. A significant advantage of our approach is that many existing optimization methods can be used to search optimized compositions, where parallel or choice structure is enabled, individual service with multiple input or output parameters is allowed.

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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