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Robust Feedback Control Design for a Nonlinear Wastewater Treatment Model

M. Serhani, N. Raissi, P. Cartigny (2009)

Mathematical Modelling of Natural Phenomena

In this work we deal with the design of the robust feedback control of wastewater treatment system, namely the activated sludge process. This problem is formulated by a nonlinear ordinary differential system. On one hand, we develop a robust analysis when the specific growth function of the bacterium μ is not well known. On the other hand, when also the substrate concentration in the feed stream sin is unknown, we provide an observer of system and propose a design of robust feedback control in...

Robust numerical approximation of coupled Stokes' and Darcy's flows applied to vascular hemodynamics and biochemical transport*

Carlo D'Angelo, Paolo Zunino (2011)

ESAIM: Mathematical Modelling and Numerical Analysis

The fully coupled description of blood flow and mass transport in blood vessels requires extremely robust numerical methods. In order to handle the heterogeneous coupling between blood flow and plasma filtration, addressed by means of Navier-Stokes and Darcy's equations, we need to develop a numerical scheme capable to deal with extremely variable parameters, such as the blood viscosity and Darcy's permeability of the arterial walls. In this paper, we describe a finite element method for...

Robust numerical approximation of coupled Stokes' and Darcy's flows applied to vascular hemodynamics and biochemical transport*

Carlo D'Angelo, Paolo Zunino (2011)

ESAIM: Mathematical Modelling and Numerical Analysis

The fully coupled description of blood flow and mass transport in blood vessels requires extremely robust numerical methods. In order to handle the heterogeneous coupling between blood flow and plasma filtration, addressed by means of Navier-Stokes and Darcy's equations, we need to develop a numerical scheme capable to deal with extremely variable parameters, such as the blood viscosity and Darcy's permeability of the arterial walls. In this paper, we describe a finite element method for...

Robust sensor fault estimation for descriptor-LPV systems with unmeasurable gain scheduling functions: application to an anaerobic bioreactor

Francisco-Ronay López-Estrada, Jean-Christophe Ponsart, Didier Theilliol, Carlos-Manuel Astorga-Zaragoza, Jorge-Luis Camas-Anzueto (2015)

International Journal of Applied Mathematics and Computer Science

This paper addresses the design of a state estimation and sensor fault detection, isolation and fault estimation observer for descriptor-linear parameter varying (D-LPV) systems. In contrast to where the scheduling functions depend on some measurable time varying state, the proposed method considers the scheduling function depending on an unmeasurable state vector. In order to isolate, detect and estimate sensor faults, an augmented system is constructed by considering faults to be auxiliary state...

Rotation to physiological factors revised

Miroslav Kárný, Martin Šámal, Josef Böhm (1998)

Kybernetika

Reconstruction of underlying physiological structures from a sequence of images is a long-standing problem which has been solved by factor analysis with a success. This paper tries to return to roots of the problem, to exploit the available findings and to propose an improved paradigm.

Rule weights in a neuro-fuzzy system with a hierarchical domain partition

Krzysztof Simiński (2010)

International Journal of Applied Mathematics and Computer Science

The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results showing the advantage of their usage are presented.

Sampling properties of estimators of nucleotide diversity at discovered SNP sites

Alexander Renwick, Penelope Bonnen, Dimitra Trikka, David Nelson, Ranajit Chakraborty, Marek Kimmel (2003)

International Journal of Applied Mathematics and Computer Science

SNP sites are generally discovered by sequencing regions of the human genome in a limited number of individuals. This may leave SNP sites present in the region, but containing rare mutant nucleotides, undetected. Consequently, estimates of nucleotide diversity obtained from assays of detected SNP sites are biased. In this research we present a statistical model of the SNP discovery process, which is used to evaluate the extent of this bias. This model involves the symmetric Beta distribution of...

Scaling of Stochasticity in Dengue Hemorrhagic Fever Epidemics

M. Aguiar, B.W. Kooi, J. Martins, N. Stollenwerk (2012)

Mathematical Modelling of Natural Phenomena

In this paper we analyze the stochastic version of a minimalistic multi-strain model, which captures essential differences between primary and secondary infections in dengue fever epidemiology, and investigate the interplay between stochasticity, seasonality and import. The introduction of stochasticity is needed to explain the fluctuations observed in some of the available data sets, revealing a scenario where noise and complex deterministic skeleton...

Seasonal Forcing Drives Spatio-Temporal Pattern Formation in Rabies Epidemics

N. V. Festenberg, T. Gross, B. Blasius (2010)

Mathematical Modelling of Natural Phenomena

Seasonal forcing is identified as a key pattern generating mechanism in an epidemic model of rabies dispersal. We reduce an established individual-based high-detail model down to a deterministic conceptual model. The characteristic wave pattern characterized by high densities of infected individuals is maintained throughout the reduction process. In our model it is evident that seasonal forcing is the dominant factor that drives pattern formation. In particular we show that seasonal forcing can...

Seasonality, Climate Cycles and Body Size Evolution

T. A. Troost, J. A. van Dam, B. W. Kooi, E. Tuenter (2009)

Mathematical Modelling of Natural Phenomena

The seasonality hypothesis states that climates characterized by large annual cycles select for large body sizes. In order to study the effects of seasonality on the evolution of body size, we use a model that is based on physiological rules and first principles. At the ecological time scale, our model results show that both larger productivity and seasonality may lead to larger body sizes. Our model is the first dynamic and process-based model to support the seasonality hypothesis and hence...

Segmentation of breast cancer fine needle biopsy cytological images

Maciej Hrebień, Piotr Steć, Tomasz Nieczkowski, Andrzej Obuchowicz (2008)

International Journal of Applied Mathematics and Computer Science

This paper describes three cytological image segmentation methods. The analysis includes the watershed algorithm, active contouring and a cellular automata GrowCut method. One can also find here a description of image pre-processing, Hough transform based pre-segmentation and an automatic nuclei localization mechanism used in our approach. Preliminary experimental results collected on a benchmark database present the quality of the methods in the analyzed issue. The discussion of common errors and...

Segmentation of MRI data by means of nonlinear diffusion

Radomír Chabiniok, Radek Máca, Michal Beneš, Jaroslav Tintěra (2013)

Kybernetika

The article focuses on the application of the segmentation algorithm based on the numerical solution of the Allen-Cahn non-linear diffusion partial differential equation. This equation is related to the motion of curves by mean curvature. It exhibits several suitable mathematical properties including stable solution profile. This allows the user to follow accurately the position of the segmentation curve by bringing it quickly to the vicinity of the segmented object and by approaching the details...

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