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Featured researches published by Vania Rangelova.


Chapter 5, in : Intelligent and Biosensors | 2010

Soft Computing Techniques in Modelling the Influence of pH and Temperature on Dopamine Biosensor

Vania Rangelova; Diana Tsankova; Nina Dimcheva

Biosensors represent very promising analytical tools that are capable of providing a continuous, fast and sensitive quantitative analysis in a straightforward and cost-effective way. According to the definition of IUPAC (International Union of Pure and Applied Chemistry) the biosensing analytical devices combine a biological element for molecular recognition with a signal-processing device (transducer). The transducer, which normally ensures the high sensitivity of the sensor, can be thermal, optical, magnetic field, piezoelectrical or electrochemical. On the other hand, the selectivity of detection is assured by the biological recognition element that might consists of either a bioligand (DNA, RNA, antibodies etc.) or a biocatalyst, such as some redox proteins, individual enzymes and enzymatic systems (cell membranes, whole microorganisms, tissues) (Castillo et al., 2004; Scheller et al. 2001). Electrochemical biosensors show two main advantages over the other types of biosensors: i) they are susceptible to miniaturization, and ii) the electrical response – current or potential, could be easily processed using not expensive and compact instrumentation. Among the electrochemical biosensors, enzyme-based amperometric biosensors represents the most used group, which functions on the basis of monitoring the current variation at an polarised electrode, induced by the reaction/interaction of the biorecognition element with the analyte of interest. Then, amperometric enzyme-based biosensors on their part, can be classified into three categories (Castillo et al., 2004; Scheller et al., 2001), in accordance with the mode of action: first generation biosensors: the signal is generated upon the electrochemical reaction of an active reagent (monitoring the decrease of the current) or product (monitoring the increase of the current) that are involved in the biochemical transformation of the target compoundthe enzyme substrate (Dimcheva et al., 2002 ; Dodevska et al., 2006; Horozova et al., 2009). second generation biosensors: the architecture of these biosensors includes a freely diffusing redox mediator (small molecular weight compounds, able to effectively shuttle electrons between the electrode surface and the enzyme active site) and in this


intelligent data acquisition and advanced computing systems technology and applications | 2017

Complex criteria for assessing the quality of biosensor systems

Pavlina Kacarova; Vania Rangelova; Agata Manolova

Biosensor systems (BSS) have been examined like object of diagnostic with all their parameters and their characteristics being analyzed. For example the known generalized parameter Thiles module, depends on constructive parameters of the biosensors and reflects their technical characteristics. The factor of accuracy is another generalized indicator reflecting mainly metrological characteristics. But there is a necessity to introduce another theoretical mathematical formulation for an indicator which will generalize both metrological and technical characteristics of biosensor systems. Such criterion is a generalized indicator for assessment of the quality of the biosensor, which is at the top level of the hierarchy diagram. It gives an opportunity to compare the different constructions of biosensor systems and can be used as a numerical criterion for assessment of their quality.


Scientific-professional journal of technical faculties of the University of Osijek | 2009

APPLICATION OF GENETIC ALGORITHMS FOR DETERMINING THE PARAMETERS OF INDUCTION MOTORS

I Kostov; V Spasov; Ivan Kostov; Vasil Spasov; Vania Rangelova


international conference on biomedical engineering | 2007

CMAC-based modelling the influence of temperature on tissue biosensor for measurement of dopamine

Vania Rangelova; Diana Tsankova


international conference on biomedical engineering | 2007

Cancer outcome prediction by cluster-based artificial immune networks

Diana Tsankova; Vania Rangelova


Proc. of II inter.symp “ Instrumentation Science and Technology- ISIST2002” | 2002

INVESTIGATION OF REPEATABILITY AND ERROR INSTABILITY ANALYSIS OF TISSUE BIOSENSOR

Vania Rangelova; I. N. Kodjabashev; Neykov Al


Journal of Engineering Annals of the Faculty of engineering Huhedoara | 2010

PARAMETER ESTIMATION OF BIOSENSOR SYSTEM USING GENETIC ALGORITHM

Vania Rangelova; Vasil Spasov; Pavlina Katsarova


Journal of Engineering Annals of the Faculty of engineering Huhedoara | 2010

INHIBITOR MULTIENZYME BIOSENSOR SYSTEM IN DYNAMIC MODE - FLUORIDE MEASUREMENT

Vania Rangelova; Antonia Pandelova; Nikolay Stoyanov


International Journal of Engineering, University Politehnica Timisoara, Faculty of Engineering Hunedoara, | 2010

POWER FACTOR DETERMINATION OF INDUCTION MOTOR FREQUENCY CONTROLLED DRIVES

Ivan Kostov; Vania Rangelova


Tehnicki Vjesnik-technical Gazette | 2009

Primjena genetskih algoritama za utvrđivanje parametara asinkronog motora

Ivan Kostov; Vasil Spasov; Vania Rangelova

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Diana Tsankova

Technical University of Sofia

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Ivan Kostov

Technical University of Sofia

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Vasil Spasov

Technical University of Sofia

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Agata Manolova

Technical University of Sofia

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Pavlina Kacarova

Technical University of Sofia

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