Seminar for
DECISION MAKING – THEORY, TECHNOLOGY AND PRACTICE

 

PROGRAM

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Plan rada Seminara Odlučivanje - teorija, tehnologija, praksa za NOVEMBAR 2021.

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ČETVRTAK, 04.11.2021. u 13:00, Live stream Niš
Jovan Ćirić, Faculty of Electronic Engineering in Niš
FRESHWATER ALGAE AS GREEN ENERGY PRODUCERS AND THEIR UTILISATION POTENTIAL OF WASTE GLYCEROL OBTAINED IN BIODIESEL PRODUCTION
Algae offer solutions for many problems of our civilization. Biotechnological applications of algae have become a part of modern reality. As one of the many application possibilities, algae can be used as a renewable energy source. Algae can store energy in the form of oil that can be an appropriate raw material for biodiesel production. Microalgae are especially significant because of their high growth rate, high oil content, and ability to grow in an unfavorable environment for agriculture. Also, the cultivation of microalgae can improve the reduction of carbon dioxide emissions. With the great rise in the industrial production of biodiesel worldwide in recent years, great amounts of glycerol have been created and the sale price of pure and waste glycerol has decreased notably. Pure glycerol is a consequential commercial raw material with broad implementation in the pharmaceutical, cosmetic, chemical and food industry but waste glycerol corresponds as a promising raw material for some innovative and new processes. As one of the possibilities of its usage is as a carbon source in microbial growth media for fermentative industry and the production of commercially important products. In this presentation, the results of the research a possibility of waste glycerol, obtained in sunflower and rapeseed oil-based biodiesel production, usage by microalgae in the interest of obtaining the microbial oil as a raw material are presented.

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ČETVRTAK, 18.11.2021. u 13:00, Live stream Niš
Radmila Janković Babić, Mathematical Institute of the Serbian Academy of Science and Arts
APPLICATION OF MACHINE LEARNING TECHNIQUES FOR PREDICTION OF ECOLOGICAL FOOTPRINT
Machine learning techniques are nowadays widely applied in different research areas including medicine, ecology, transportation, and industrial production. With the growing need to meet the sustainability goals of the United Nation’s Agenda 2030, there is also the need to predict the amount of available natural resources, especially from the energy perspective. In this research, three machine learning algorithms were used to predict the values of the ecological footprint based on a set of energy parameters and population numbers. The predictions were made using k-nearest neighbor (KNN) regression, artificial neural networks (ANN), and random forest (RF) regression. The hyper-parameters of each model were optimized using the Tree-structured Parzen Estimator (TPE). The research showed that the values of ecological footprint can be most accurately predicted using the KNN algorithm.

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ČETVRTAK, 25.11.2021. u 13:00, Live stream Niš
Andjelka N. Hedrih, Mathematical Institute of the Serbian Academy of Science and Arts
TORSION OSCILLATIONS OF BIOMECHANICAL MODEL OF TREE STEM WITH BRANCHES
Making mechanical models of torsion oscillations of tree stem with branches is very challenging and can be done through a variety of approaches e.g.: experimental, finite element method approach, and theoretical mathematical/mechanical models. Most of the mechanical models cover bending behaviour. Here, we use an oscillatory model in a form of a hybrid discrete biodynamical system of complex structures. The description of the model will be given. Free and forced eigen main modes of fractional-type torsion oscillations were analysed using a system of ordinary differential fractional order equations. Energy dissipation of the system is defined for inhomogeneous fractional type system. The concept of fractal type discrete chain-string structure is introduced. The benefit of this concept is a possibility to analyse torsion oscillations of more complex structures. The presented model is suitable for analysing torsion oscillations of tree stems with different types of branching, indifferent developmental stages (young/old, with different stem and branch diameter…).

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Predavanja su namenjena sirokom krugu slusalaca, ukljucujuci studente redovnih i doktorskih studija. Seminar će se održavati svakog drugog četvrtka od 13:00 - 14:00^h, CIITLAB, Elektronski fakultet Niš, Aleksandra Medvedeva 14, Niš

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