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Papers by Svetla Vassileva

Studies in Environmental Science, 1991

ABSTRACT This chapter explores some bioenergetic factors SO, σ, Γ, γT, and their impact on biogas... more ABSTRACT This chapter explores some bioenergetic factors SO, σ, Γ, γT, and their impact on biogas and ethanol output in laboratory conditions. The chapter discusses to create a mathematical model, which could be used for predicting the process of productivity and rentability. The design of mathematical models simulating the behavior on real systems on a computer is an important aspect of the methodology of present day engineering analysis. The models presented in this work are formulated by using experimental data summarizing the biochemical and physiological aspects of the methanogenesis. Increasing accumulation of industrial, agricultural and municipal wastes have a serious impact on the ecological equilibrium. These wastes are a valuable raw material for obtaining energy rich compounds, such as various alcohols and methane, yet their storage more often than not is very difficult. That is why the creation of technologies including recycling of waste in industry, and agriculture is a primary task. The experimental data are presented in mathematical models, describing process productivity as a function of bioenergetic factors.

Abstract: By antiquity humanity seeks to discover likeness principles of human behavior, moving, ... more Abstract: By antiquity humanity seeks to discover likeness principles of human behavior, moving, sensing, thinking, evaluating and creating. In this connection our paper presents a short survey of history and advances of artificial intelligence. AI research is highly technical and specialized, and is strongly divided into sub-fields that often fail to communicate with each other. Some of the division is due to social and cultural factors: sub-fields have grown up around particular institutions and the work of individual researchers. AI research is also divided by several technical issues. Some sub-fields focus on the solution of specific problems. Others focus on one of several possible approaches or on the use of a particular tool or towards the accomplishment of particular applications. The paper observes a period from ancient centuries until recent advances of this interesting scientific field.

2013 Signal Processing Symposium (SPS), 2013

ABSTRACT The present paper is an attempt for acceptable balance between theoretical research, com... more ABSTRACT The present paper is an attempt for acceptable balance between theoretical research, computer simulations and experiments on real industrial objects. Several rules and recommendations are retrieved from the obtained results about the exploitation domains of certain classes of industrial metallurgical objects. The practical trend of the presented results is contained in our efforts for a comparative analysis and also to form rules of the presented methods for intelligent predictive diagnostics. An original method is proposed for predictive maintenance of a metallurgical ladle based on simulations of diagnostics and forecasting of the current state of high-temperature objects. Knowing the condition of the insulation of metallurgical ladles especially at the end of the campaign is essential for operational management in a case of local damage.

Cybernetics and Information Technologies, 2012

The paper presents an overview of the image-processing techniques. The set of basic theoretical i... more The paper presents an overview of the image-processing techniques. The set of basic theoretical instruments includes methods of mathematical analysis, linear algebra, probability theory and mathematical statistics, theory of digital processing of one-dimensional and multidimensional signals, wavelet-transforms and theory of information. This paper describes a methodology that aims to detect and diagnose faults, using thermographs approaches for the digital image processing technique.

Biotechnology & Biotechnological Equipment, 2010

ABSTRACT Brewing fermentation is among the most well studied processes in the food industry. Neve... more ABSTRACT Brewing fermentation is among the most well studied processes in the food industry. Nevertheless, the process still provides challenges to the brewers. It is subject to alteration stemming from the variation in the yeast, a living organism, and due to the complex raw materials of biological origin. With a reliable predictors- artificial intelligence (AI)-based software tools as well as software analyzers for the fermentation monitoring and control one could manage with fewer measurements especially when an early warning gives the operators time to make corrective actions. Our work summarizes research results obtained in intelligent software tools design for beer manufacturing carried out in the Institute of Control and System Research and Institute of Cryobiology and Food Technologies as an answer of world trend in knowledge-based bio-economy establishment.

Comput. Informatics, 2014

Recent industry requires efficient fault discovering and isolation solutions in process equipment... more Recent industry requires efficient fault discovering and isolation solutions in process equipment service. This problem is a real-world problem of typically ill-defined systems, hard to model, with large-scale solution spaces. Design of precise models is impractical, too expensive, or often non-existent. Support service of equipment requires generating models that can analyze the equipment data, interpreting the past behavior and predicting the future one. These problems pose a challenge to traditional modeling techniques and represent a great opportunity for the application of AI-based methodologies, which enable us to deal with imprecise, uncertain data and incomplete domain knowledge typically encountered in real-world applications. In this paper the state of the art, theoretical background of conventional and AI-based techniques in support of service tasks and illustration of some applications to process equipment service on bio-ethanol production process are shortly described.

Present work is oriented to study of processes of microbial ecology by developing and implementin... more Present work is oriented to study of processes of microbial ecology by developing and implementing artificial neural networks (ANN)-based software analyzers. Microbial ecology investigates the function of microorganisms in the environment. Towards understanding the role of microorganisms in important ecosystem processes, one example is considered. The presented example is focused on continuous yeasts growth prediction by the developed software analyzer, which helps to discover the influence of initial formaldehyde concentrations on the continuous cell growth, correlated with the protein-synthesizing ability (A,[h-1]) of yeasts strain Candida didensii 74-10 at two different dilution rates (D,[h-1]). The Levenberg-Marquardt optimization technique has been used to upgrade the network by minimizing the sum square error (SSE). The performance of the network with two hidden layers for predicting cell mass and protein synthesizing ability is found to be very effective.

The task of diagnosis is to find an explanation for a set of observations and – in the case of pr... more The task of diagnosis is to find an explanation for a set of observations and – in the case of prognosis – to forecast the course of events. Diagnosis can be broken down into anomaly detection and failure identification, depending on the desired granularity of information required. Prognosis is concerned with incipient failure detection, margin prediction, or overall performance prediction. The latter can be prediction of efficiency, current system status, etc. The outcome of diagnosis and prognosis processes drives planning and execution. Fault isolation task can only be realized if the fault to be isolated has been previously taken into account in the model. There are different approaches for the design of diagnostic observers: the geometric methods, algebraic methods, spectral theory-based methods and frequency domain solutions. In our paper a two-step procedure is commonly employed for data-driven fault detection. A model that represents the normal operation conditions is first ...

IFAC Proceedings Volumes

Abstract Neural network - model-based predictive control (NN-MBPC) has not been widely used in in... more Abstract Neural network - model-based predictive control (NN-MBPC) has not been widely used in industrial biotechnology in comparison with other MBPC industrial applications. This is mainly because accurate models are usually not available for nonlinear biotechnological processes. NN allow obtaining a high accuracy in the modelling. The presented controller design show approaches to deal with the lack of the theory of non-linear systems in case one needs to identify a NN presenting MBPC structure. The described approaches based on linear and non-linear optimisation are demonstrated on the temperature controller design in a batch bioreactor. The simulations are obtained by implementing MATLAB 4.2 with Simulink.