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» Enterprise application deployment: A model driven approach
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TMI
2008
138views more  TMI 2008»
15 years 5 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
BMCBI
2007
182views more  BMCBI 2007»
15 years 6 months ago
Hybrid elementary flux analysis/nonparametric modeling: application for bioprocess control
Background: The progress in the "-omic" sciences has allowed a deeper knowledge on many biological systems with industrial interest. This knowledge is still rarely used ...
Ana P. Teixeira, Carlos Alves, Paula M. Alves, Man...
EICS
2009
ACM
15 years 11 months ago
StateStream: a developer-centric approach towards unifying interaction models and architecture
Complex and dynamic interaction behaviors in applications such as Virtual Reality (VR) systems are difficult to design and develop. Reasons for this include the complexity and lim...
Gerwin de Haan, Frits H. Post
SLE
2009
Springer
16 years 27 days ago
Ontological Metamodeling with Explicit Instantiation
Model Driven Engineering (MDE) is a promising paradigm for development. It raises the level of abstraction in software development by treating models as primary artifacts. The prac...
Alfons Laarman, Ivan Kurtev
CMG
2001
15 years 7 months ago
Software That Can Think and Do
Rapid advances in research and technology now allow data analysis and modeling of extremely complex systems. Methods from artificial intelligence (AI) such as Neural Networks have...
Bernard Domanski