The use of computer software in the fields of engineering, technology and management has become inevitable these days. Engineering problems are tedious and time consuming to solve manually due to higher complexity. In this perspective mathematical bioscience is an emerging field that involves formulation of biological concepts in terms of equations and application of computers to solve them. Though the biological systems are very complex and beautifully constructed they obey the rules of chemistry and physics that make them susceptible to engineering analysis. This forms the basis for bioprocess modeling optimization and simulation which can be accomplished using software. In the microbial world, varieties of species are available and both in natural systems and commercial applications mixed culture operations play a vital role. In such case interaction among them decides the output of the system and five patterns of interactions (namely neutralism, amensalism, competition, commensalism, mutualism, predation and parasitism) are observed so far. In the present work an innovative and unified approach is developed to characterize these patterns of interactions among microorganisms for two species interaction. The models for pure and mixed culture growth were derived from experimental data in batch mode using CFTOOL kit in MATLAB 7.1. The differential equations were solved using ODE SOLVER in MATLAB 7.1 and the simulation studies for continuous operations were carried out using C++ software. The simulated results and their interpretations are obtained using surface plots drawn using MINITAB software.

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Radar polarimetry polarization synthetic aperture radar wetland target decomposition speckle classification