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Change-point Detection for Piecewise Deterministic Markov Processes, Alice Cleynen and Benoîte De Saporta.ĥ. Space–Time Simulations of Extreme Rainfall: Why and How?, Gwladys Toulemonde, Julie Carreau and Vincent Guinot.Ĥ. Sophie Dabo-Niang, Papa Ngom, Ndiaga Thiam, Massal Fall and Patrice Brehmer.ģ. Nonparametric Prediction for Spatial Dependent Functional Data: Application to Demersal Coastal Fish off Senegal, Mamadou N'Diaye,

Deviations From the Law of Large Numbers and Extinction of an Endemic Disease, Étienne Pardoux.Ģ.

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Mathematical Modeling of Random and Deterministic Phenomena is aimed at expert readers, young researchers, plus graduate and advanced undergraduate students who are interested in probability, statistics, modeling and mathematical analysis. The second is devoted to a modelization with interdisciplinarity in ecological, socio-economic, epistemological, demographic and social problems. The first is devoted to some advanced mathematical problems regarding epidemic models predictions of biomass space-time modeling of extreme rainfall modeling with the piecewise deterministic Markov process optimal control problems evolution equations in a periodic environment and the analysis of the heat equation. The chapters can be read independently of each other, with dedicated references specific to each chapter. As such, it provides current research in mathematics, with applications in biological and environmental sciences, ecology, epidemiology and social perspectives. This book highlights mathematical research interests that appear in real life, such as the study and modeling of random and deterministic phenomena.

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Software Pty Ltd (formerly Myriax Software Pty Ltd), is carefully examined. Finally, a comparative result over experimental data of ECOPAMPA against Echoview

These algorithms are implemented within the ECOPAMPA software, which is the first Argentinean system for marine species identification.

This article also describes thoroughly the digital processing algorithms for this automatic detection and classification, as well as the automatic process required for surface and bottom line detection, which is necessary to determine the exploration range. To accomplish this task it was necessary to have a development platform that allowed reading echo data from a particular echosounder, to detect fish aggregations and then to calculate fish school descriptors that would be used for fish-species identification, in an automatic way.

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Within it, it is discussed how to obtain energetic, morphometric and bathymetric fish school descriptors to accurately identify different fish-species. A software architecture for echo data processing is presented in this article. Accurate identification of aquatic organisms and their numerical abundance calculation using echo detection techniques remains a great challenge for marine researchers.