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This paper presents a hybrid scheme based on two population-based metaheuristic techniques, namely genetic algorithm (GA) and cuckoo search (CS). In particular, the hybrid is formed by the application of standard simple genetic algorithms (SGA) and CS, specifically adapted and for first time applied by the authors for the purposes of parameter identification of yeast fed-batch fermentation process model. The parameters of the hybrid technique SGA-CS have been thoroughly explored and tuned to meet the specific peculiarities of the considered here optimization problem. A comparison of SGA, CS and developed hybrid SGA-CS has been performed, outlining the advantages and disadvantages of each algorithm. Additionally, a new modification of SGA-CS hybrid technique, inspired by proven as very effective modification of SGA, working with implementation of main genetic operators in order crossover, mutation and selection, has been here elaborated. Presented modified hybrid technique has been tested, aiming at verification of the obtained promising results of developed SGA-CS technique.

Proximal humeral fractures are common injuries and they occur primarily in older patients. They represent 5.7% of diagnosed fractures and are the third most common fracture pattern seen in elderly. Fractures of the proximal humerus usually occur after a high or low energy fall. Due to the variety of factors, which influence the classification, and the diagnosis of these fractures, early detection is the key factor for an appropriate treatment. Accordingly, in this study we present a successful example of Generalized Nets application in traumatology and propose a novel approach to timely detection and diagnosing of proximal humeral fractures.

The implementation of functional state approach for modelling of biotechnological processes is considered in this paper. This concept helps in monitoring and control of complex processes such as bioprocesses. Using of functional state modelling approach for biotechnological processes aims to overcome the main disadvantage of using global process model, namely complex model structure and big number of model parameters, which complicate the model simulation and parameter estimation. The main advantage of functional state modelling is that the parameters of each local model can be separately estimated from other local models parameters.

This paper presents the implementation of functional state approach to modelling of Escherichia coli fed-batch cultivation. Due to the complex metabolic pathways of microorganisms, the accurate modelling of bioprocesses is rather difficult. The functional state approach of a process is an alternative concept which helps in modelling and control of complex processes. The approach main idea is developing of models based on multiple submodels for each functional states (operating regime). In each functional state the process is described by a conventional type of model, called the local model, which is valid in this state. For parameter identification of the model the genetic algorithms are used. Genetic algorithms are directed random search techniques, applying the mechanics of natural selection and natural genetics, which can find the global optimal solution in complex multidimensional search spaces. Based on the available experimental data and simulations of E. coli fed-batch cultivation it is sho...

In this paper, the functional state modelling approach is validated for modelling of the cultivation of two different microorganisms: yeast (Saccharomyces cerevisiae) and bacteria (Escherichia coli). Based on the available experimental data for these fed-batch cultivation processes, three different functional states are distinguished, namely primary product synthesis state, mixed oxidative state and secondary product synthesis state. Parameter identification procedures for different local models are performed using genetic algorithms. The simulation results show high degree of adequacy of the models describing these functional states for both S. cerevisiae and E. coli cultivations. Thus, the local models are validated for the cultivation of both microorganisms. This fact is a strong structure model verification of the functional state modelling theory not only for a set of yeast cultivations, but also for bacteria cultivation. As such, the obtained results demonstrate the efficiency and efficacy of the functional state modelling approach.

The paper presents the implementation of multiple model approach to modelling of Escherichia coli BL21(DE3)pPhyt109 fed-batch cultivation processes for an extracellular production of bacterial phytase. Due to the complex metabolic pathways of microorganisms, the accurate modelling of bioprocesses is rather difficult. Multiple model approach is an alternative concept which helps in modelling and control of complex processes. The main idea is the development of a model based on simple submodels for the purposes of further high quality process control. The presented simulations of E. coli fed-batch cultivation show how the process could be divided into different functional states and how the model parameters could be obtained easily using genetic algorithms. The obtained results and model verification demonstrate the effectiveness of the applied concept of multiple model approach and of the proposed identification scheme. © 2007 by Pontificia Universidad Católica de Valparaíso.

An application of functional states modelling approach for aerobic batch baker's yeast fermentation is presented in this paper. The functional states help in monitoring and control of complex processes such as bioprocesses. The main idea is to use a two-level hierarchy where on the top level the process is divided into macrostates, called functional states, according to behavioural equivalence. In a functional state, the process is described by a conventional type of model, called local model, which is valid in this functional state. To illustrate the concept of functional states in fermentation processes, experimental data and simulations of an aerobic batch baker's yeast fermentation are presented.

In this paper biotechnological processes (BTP) as objects with distributed parameters are considered. On the base of mass conservation law in the system, the equations of the material balance for substrate S with or without rendering of the diffusion phenomena in the system are obtained. The theory of semi- groups linear restricted operators is applied for designed mathematical models of BTP. An objects' description in state space is presented on the base of a pre- defined infinitesimal operator. The analytical solutions, obtained after the application of the theory of semi- groups linear restricted operators, prove the efficiency of the developed procedure.