scholarly journals Asymptotic Shape and Propagation of Fronts for Growth Models in Dynamic Random Environment

2011 ◽  
pp. 195-223 ◽  
Author(s):  
Harry Kesten ◽  
Alejandro F. Ramı́rez ◽  
Vladas Sidoravicius
Keyword(s):  
Random Environment ◽  
Growth Models ◽  
Asymptotic Shape

scholarly journals Asymptotic shape and the speed of propagation of continuous-time continuous-space birth processes

2018 ◽  
Vol 50 (01) ◽  
pp. 74-101 ◽  
Author(s):  
Viktor Bezborodov ◽  
Luca Di Persio ◽  
Tyll Krueger ◽  
Mykola Lebid ◽  
Tomasz Ożański
Keyword(s):  
Continuous Time ◽  
Birth Rate ◽  
Growth Models ◽  
Classical Lattice ◽  
Continuous Space ◽  
Asymptotic Shape ◽  
Subadditive Ergodic Theorem ◽  
Speed Of Propagation ◽  
Birth Processes ◽  
Precise Expression

AbstractWe formulate and prove a shape theorem for a continuous-time continuous-space stochastic growth model under certain general conditions. Similar to the classical lattice growth models, the proof makes use of the subadditive ergodic theorem. A precise expression for the speed of propagation is given in the case of a truncated free-branching birth rate.

scholarly journals Asymptotic shape for the contact process in random environment

2012 ◽  
Vol 22 (4) ◽  
pp. 1362-1410 ◽  
Author(s):  
Olivier Garet ◽  
Régine Marchand
Keyword(s):  
Random Environment ◽  
Contact Process ◽  
Asymptotic Shape

Growth Phenomena in Cellular Automata

2003 ◽  
Author(s):  
Janko Gravner
Keyword(s):  
Cellular Automata ◽  
Growth Models ◽  
Research Literature ◽  
Diffusion Limited Aggregation ◽  
Asymptotic Shape ◽  
Growth Properties ◽  
To Come ◽  
Initial Seed ◽  
Selling Point ◽  
Simple Growth

We illustrate growth phenomena in two-dimensional cellular automata (CA) by four case studies. The first CA, which we call Obstacle Course, describes the effect that obstacles have on such features of simple growth models as linear expansion and coherent asymptotic shape. Our next CA is random-walk-based Internal Diffusion Limited Aggregation, which spreads sublinearly, but with a shape which can be explicitly computed due to hydrodynamic effects. Then we propose a simple scheme for characterizing CA according to their growth properties, as indicated by two Larger than Life examples. Finally, a very simple case of Spatial Prisoner’s Dilemma illustrates nucleation analysis of CA. In essence, analysis of growth models is an attempt to study properties of physical systems far from equilibrium (e.g., Meakin [34] and more than 1300 references cited in the latter). Cellular automata (CA) growth models, by virtue of their simplicity and amenability to computer experimentation [25], have become particularly popular in the last 20 years, especially in physics research literature [40, 42]. Needless to say, precise mathematical results are hard to come by, and many basic questions remain completely open at the rigorous level. The purpose of this chapter, then, is to outline some successes of the mathematical approach and to identify some fundamental difficulties. We will mainly address three themes which can be summarized by the terms: aggregation, nucleation, and constraint-expansion transition. These themes also provide opportunities to touch on the roles of randomness, monotonicity, and linearity in CA investigations. We choose to illustrate these issues by particular CA rules, with little attempt to formulate a general theory. Simplicity is often, and rightly, touted as an important selling point of cellular automata. We have, therefore, tried to choose the simplest models which, while being amenable to some mathematical analysis, raise a host of intriguing unanswered questions. The next few paragraphs outline subsequent sections of this chapter. Aggregation models typically study properties of growth from a small initial seed. Arguably, the simplest dynamics are obtained by adding sites on the boundary in a uniform fashion.

Driven periodic structures in random environment

1999 ◽  
Vol 09 (PR10) ◽  
pp. Pr10-85-Pr10-87
Author(s):  
V. M. Vinokur
Keyword(s):  
Random Environment ◽  
Periodic Structures

Driven elastic system in a random environment

1999 ◽  
Vol 09 (PR10) ◽  
pp. Pr10-69-Pr10-71 ◽  
Author(s):  
P. Chauve ◽  
T. Giamarchi ◽  
P. Le Doussal
Keyword(s):  
Random Environment ◽  
Elastic System

APPLICATION OF SPC AND GROWTH MODELS ON THE ECONOMIC TRAJECTORY OF THE LEATHER AND FOOTWEAR INDUSTRY

2020 ◽  
Author(s):  
Mario Lesina ◽  
Lovorka Gotal Dmitrovic
Keyword(s):  
Human Capital ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Growth Models ◽  
Pearson Correlation ◽  
Small Companies ◽  
Statistical Process ◽  
Production Staff ◽  
Footwear Industry

The paper shows the relation among the number of small, medium and large companies in the leather and footwear industry in Croatia, as well as the relation among the number of their employees by means of the Spearman and Pearson correlation coefficient. The data were collected during 21 years. The warning zone and the risk zone were determined by means of the Statistical Process Control (SPC) for a certain number of small, medium and large companies in the leather and footwear industry in Croatia. Growth models, based on externalities, models based on research and development and the AK models were applied for the analysis of the obtained research results. The paper shows using the correlation coefficients that The relation between the number of large companies and their number of employees is the strongest, i.e. large companies have the best structured work places. The relation between the number of medium companies and the number of their employees is a bit weaker, while there is no relation in small companies. This is best described by growth models based on externalities, in which growth generates the increase in human capital, i.e. the growth of the level of knowledge and skills in the entire economy, but also deductively in companies on microeconomic level. These models also recognize the limit of accumulated knowledge after which growth may be expected. The absence of growth in small companies results from an insufficient level of human capital and failure to reach its limit level which could generate growth. According to Statistical Process Control (SPC), control charts, as well as regression models, it is clear that the most cost-effective investment is the investment into medium companies. The paper demonstrates the disadvantages in small, medium and large companies in the leather and footwear industry in Croatia. Small companies often emerge too quickly and disappear too easily owing to the employment of administrative staff instead of professional production staff. As the models emphasize, companies need to invest into their employees and employ good production staff. Investment and support to the medium companies not only strengthens the companies which have a well-arranged technological process and a good systematization of work places, but this also helps large companies, as there is a strong correlation between the number of medium and large companies.

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