By Bruno Sericola, Telek Miklós, Gábor Horváth
This ebook constitutes the refereed complaints of the twenty first foreign convention on Analytical and Stochastic Modelling options and functions, ASMTA 2014, held in Budapest, Hungary, in June/July 2014. The 18 papers provided have been rigorously reviewed and chosen from 27 submissions. The papers speak about the newest advancements in analytical, numerical and simulation algorithms for stochastic structures, together with Markov methods, queueing networks, stochastic Petri nets, method algebras, video game idea, etc.
Read Online or Download Analytical and Stochastic Modeling Techniques and Applications: 21st International Conference, ASMTA 2014, Budapest, Hungary, June 30 – July 2, 2014. Proceedings PDF
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Extra info for Analytical and Stochastic Modeling Techniques and Applications: 21st International Conference, ASMTA 2014, Budapest, Hungary, June 30 – July 2, 2014. Proceedings
The following two functions represent the feedback regulating proliferation: Markovian Agents Population Models to Study Cancer Evolution ωCSC , 1 + hCSC ST C (t) ωP C ωP C (t) = , 1 + hP C ST C (t) ωCSC (t) = 25 (9) (10) where hCSC and hP C deﬁne the strength of the feedback. Notice that, in equations (9),(10) the number of TCs acts as a brake on cell growth, being CSC and PC proliferation rates deﬁned as decreasing functions of this quantity. Indeed, a high number of cells in the system induces a decrease in the cell proliferation rates.
As shown in Fig. 1, the predominant early theories of disease causation were mostly supernatural, astronomical or religious, with causal agents including evil spirits, planetary motion and divine retribution. From the Middle Ages until Victorian times, it was also believed that if one inhaled miasmas – toxic vapors that emanated from swamps or decaying organic matter – disease would result . Progress towards a more scientiﬁc and data–based approach began to be made from 1600 onwards with the collection of the ﬁrst public health statistics, by John Graunt (1620–1674)  and others.
Springer, Heidelberg (2004) 7. : The Selﬁsh Gene. Oxford University Press, Oxford (1976) 8. : Markovian sir model for opinion propagation. In: Proceedings of the 2013 25th International Teletraﬃc Congress (ITC), pp. 1–7. IEEE (2013) 9. : Daniel Bernoulli’s epidemiological model revisited. Mathematical Biosciences 180, 1–21 (2002) 10. : Markov processes – characterization and convergence. Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Statistics. , New York (1986) 11.
Analytical and Stochastic Modeling Techniques and Applications: 21st International Conference, ASMTA 2014, Budapest, Hungary, June 30 – July 2, 2014. Proceedings by Bruno Sericola, Telek Miklós, Gábor Horváth