The main goal of this work is to introduce a theoretical model, based on cellular automata, to simulate epidemic spreading. Specifically, it divides the population into three classes: susceptible, infected and recovered, and the state of each cell stands for the portion of these classes of individuals in the cell at every step of time. The effect of population vaccination is also considered. The proposed model can serve as a basis for the development of other algorithms to simulate real epidemics based on real data.
In this paper a new mathematical model for predicting the spread of a fire front in homogeneous and inhomogeneous environments is presented. It is based on a bidimensional cellular automata model, whose cells stand for regular hexagonal areas of the forest. The results obtained are in agreement with the fire spreading in real forests.
Numerical methods are tools for approximating solutions to problems that may have complicated developments or cannot be solved analytically. In engineering courses, students must address problems related other disciplines such as structural or rock mechanics, biology, chemistry or physics. Prior to solving these problems it is important to define and adopt a rational framework. The students of fourth course out of five, of the bachelor's degree in Computer Sciences or Industrial Engineering at the University of Salamanca (Spain), they learn mathematics solving real problems with the help of the already acquired interdisciplinary knowledge. We have proposed the students a term project that summarizes some of the knowledge and competences acquired during the lessons. We will describe in this study the software and specific applications that will be use during the whole course.
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