Browsing Doctoral Dissertations by Title
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MEASURING BLACK HOLE MASSES IN ACTIVE GALACTIC NUCLEI USING THE POLARIZATION OF BROAD EMISSION LINESSavić, Đorđe (Beograd , 2019)[more][less]
Abstract: Supermassive black holes (SMBHs) reside in the heart of nearly every massive galaxy in the Universe. Most of them lie dormant, but when the nearby gas is abundant, it will enter an active phase and form an active galactic nucleus (AGN). In their active phase, SMBHs have a profound effect on the host galaxy evolution and its environment. Reliable SMBH mass measuring is therefore an important task in modern astronomy. For that purpose, a method has been recently proposed by Afanasiev & Popović (2015) that uses the rotation of the polarization plane position angle across the broad emission line profile in order to trace the Keplerian motion and determine the SMBH mass. This method assumes that broad lines are emitted from a flattened disk-like region undergoing Keplerian motion, while the polarization is mainly due to the light scattering of the inner side of the coplanar dusty torus – the equatorial scattering. The goal of the thesis is to theoretically explore the possibilities of this method. We performed numerous Monte Carlo simulations for modeling equatorial scattering in AGNs using the radiative transfer code stokes (Goosmann & Gaskell 2007). We included complex motion of the emitting region in the form of radial inflows, vertical outflows, or due to the presence of the supermassive binary black holes (SMBBHs). We also selected fourwell known AGNs for observations: NGC4051, NGC4151, 3C273 and PG0844+349. Spectropolarimetry was done with the 6m telescope BTA of the Special Astrophysical Observatory of the Russian Academy of Science (SAO RAS) with the focal reducer SCORPIO. We modeled each of these AGNs using observational data available from the literature, and we compared the results of our models with observational data. We find that this method can be used as a new independent way to measure the SMBH masses in AGNs. The influence of the inflows and the outflows can be ignored if they are much lower than the Keplerian velocity. Additionally, when the scattering region is close to the broad line region, this method becomes independent of the viewing inclination. For SMBBHs, this method cannot be used, however, we obtained unique polarization profiles which are not common for a single SMBH, which could be used for identifying possible SMBBH candidates. SMBH mass estimates for the four observed AGNs are in good agreement with the masses obtained using other methods, such as the method of reverberation mapping. Method for independent SMBH mass measurements has been theoretically and experimentally verified in this work, which is very important for the future research that is dealing with the SMBH influence on its immediate environment. URI: http://hdl.handle.net/123456789/4821 Files in this item: 1
teza_Djordje_Savic.pdf ( 13.41Mb ) -
Zejnullahu, Abdullah (Priština)[more][less]
URI: http://hdl.handle.net/123456789/136 Files in this item: 1
phdAbdullahZejnullahu.pdf ( 1.513Mb ) -
Lazović, Zlatko (Beograd , 2019)[more][less]
Abstract: In the first section we present the theory on uniform spaces and measures of noncompactness in metric and uniform spaces. Next, we recall the basic concepts and properties of C∗ and W∗-algebras and Hilbert modules over these algebras with some known topologies on Hilbert W∗-module. In the second section we construct a local convex topology on the standard Hilbert module l2(A), such that any compact” operator (i.e., any operator in the norm closure of the linear span of the operators of the form maps bounded sets into totally bounded sets. In the biginning A presents unital W∗-algebra, leter on A presents unital C∗-algebra. The converse is true in the special case where A = B(H) is the full algebra of all bounded linear operators on a Hilbert space H. In the third section we define a measure of noncompactness λ on the standard Hilbert C∗-module l2(A) over a unital C∗-algebra, such that λ(E) = 0 if and only if E is A-precompact (i.e. it is ε-close to a finitely generated projective submodule for any ε > 0) and derive its properties. Further, we consider the known, Kuratowski, Hausdorff and Istratescu measure of noncompactnes on l2(A) regarded as a locally convex space with respect to a suitable topology. We obtain their properties as well as some relationships between them and above introduced measure of noncompactness. In the forth section we generalize the notion of a Fredholm operator to an arbitrary C∗-algebra. Namely, we define finite type elements in an axiomatic way, and also we define a Fredholm type element a as such an element of a given C∗-algebra for which there are finite type elements p and q such that (1−q)a(1−p) is invertible. We derive an index theorem for such operators. In subsection Corollaries we show that many well-known operators are special cases of our theory. Those include: classical Fredholm operators on a Hilbert space, Fredholm operators in the sense of Breuer, Atiyah and Singer on a properly infinite von Neumann algebra, and Fredholm operators on Hilbert C∗-modules over a unital C∗-algebra in the sense of Mishchenko and Fomenko. URI: http://hdl.handle.net/123456789/4819 Files in this item: 1
dr_Zlatko_Lazovic.pdf ( 2.019Mb ) -
Mrkela, Lazar (Beograd , 2024)[more][less]
Abstract: This dissertation examines two discrete location problems and their bi- objective variants. The first problem under consideration is the maximal covering location problem with user preferences and budget constraints imposed on facility opening. This variant of the maximal covering problem has not been previously studied in the literature. Unlike the classical maximal covering problem, the variant proposed in this dissertation includes user preferences for locations, where users are assigned to the location with opened facility that they prefer the most. Additionally, different locations have different costs for establishing facilities, and the available budget for opening facilities is limited. This problem is solved using the Variable Neighborhood Search (VNS) method, and the results were compared with the ones obtained by an exact solver on modified instances from the literature. Furthermore, an existing variant of the maximal covering problem is also addressed, which imposes the limit on the number of opened facilities instead of limiting the budget for opening facilities. The second problem examined is the regenerator placement in optical networks. In optical networks, signal quality degrades with distance, necessitating the place- ment of costly devices to restore the signal. This dissertation studies an existing model where the set of possible regenerator locations and the set of user nodes are different, defining the problem as generalized. The generalized regenerator place- ment problem in optical networks is also solved using the Variable Neighborhood Search method, with results compared to the best available solutions from the lit- erature. Bi-objective variants of these problems are defined as well. For the maximal covering location problem, user preferences are included as weighted factors in the total covered demand, forming the first objective function. The second objective function represents the number of uncovered users and aims to ensure fairness in the model. In the regenerator placement problem for optical networks, it is assumed that, due to budget constraints, uninterrupted communication between all pairs of user nodes may not be feasible. Each pair is assigned a weight, and the sum of the weights of connected pairs constitutes the first objective function, while the second objective function represents the cost of placing regenerators. These bi-objective variants are solved using an adapted multi-objective version of the Variable Neigh- borhood Search method, and the results are compared with general evolutionary algorithms. URI: http://hdl.handle.net/123456789/5750 Files in this item: 1
lazar_mrkela_doktorska_disertacija.pdf ( 17.56Mb ) -
Kovač, Nataša (Beograd , 2018)[more][less]
Abstract: Dissertation title : Metaheuristic approach for solving one class of optimization problems in transp ort Abstract : Berth Allo cation Problem incorp orates some of the most imp ortant de- cisions that have to b e made in order to achieve maximum e ciency in a p ort. Terminal manager of a p ort has to assign incoming vessels to the available b erths, where they will b e loaded/unloaded in such a way that some ob jective function is optimized. It is well known that even the simpler variants of Berth Allo cation Problem are NP-hard, and thus, metaheuristic approaches are more convenient than exact metho ds, b ecause they provide high quality solutions in reasonable compu- tational time. This study considers two variants of the Berth Allo cation Problem: Minimum Cost Hybrid Berth Allo cationProblem (MCHBAP) and Dynamic Mini- mum Cost Hybrid Berth Allo cationProblem (DMCHBAP), b oth with xed handling times of vessels. Ob jective function to b e minimized consists of the following com- p onents: costs of p ositioning, sp eeding up or waiting of vessels, and tardiness of completion for all vessels. Having in mind that the sp eed of nding high-quality solutions is of crucial imp ortance for designing an e cient and reliable decision supp ort system in container terminal, metaheuristic metho ds represent the natural choice when dealing with MCHBAP and DMCHBAP. This study examines the fol- lowing metaheuristic approaches for b oth typ es of a given problem: two variants of the Bee Colony Optimization (BCO), two variants of the Evolutionary Algorithm (EA), and four variants of Variable Neighb orho o d Search (VNS). All metaheuristics are evaluated and compared against each other and against exact metho ds inte- grated in commercial CPLEX solver on real-life instances from the literature and randomly generated instances of higher dimensions. The analysis of the obtained results shows that on real-life instances all metaheuristics were able to nd optimal solutions in short execution times. Randomly generated instances were out of reach for exact solver due to time or memory limits, while metaheuristics easily provided high-quality solutions in short CPU time in each run. The conducted computational analysis indicates that metaheuristics represent a promising approach for MCHBAP and similar problems in maritime transp ortation. The results presented in this pap er represent a contribution to the elds of combinatorial optimization, op erational research, metaheuristic metho ds, and b erth allo cation problem in the container terminals. URI: http://hdl.handle.net/123456789/4747 Files in this item: 1
N_Kovac-doktorska_disertacija.pdf ( 3.540Mb ) -
Putnik, Stanimir (Belgrade)[more][less]
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Vrdoljak, Božo (Belgrade)[more][less]
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Đurić, Milan (Belgrade , 1965)[more][less]
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Ašković, Tomislav (Belgrade , 1976)[more][less]
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Cijan, Boris (Belgrade)[more][less]
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Čanak, Miloš (Belgrade)[more][less]
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Hotomski, Petar (Belgrade , 1982)[more][less]
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Kapunac, Stefan (Beograd , 2026)[more][less]
Abstract: This dissertation addresses methods for efficiently solving several important variants of domination problems on graphs, with a particular focus on large-scale instances that frequ- ently appear in real-world systems. Domination problems have numerous applications in the analysis and management of complex networks, including social, telecommunication, transport, and biological networks. The study covers four problems: minimum weight total domination, minimum weight independent domination, k-strong Roman domination, and the canonical mi- nimum domination problem on large graphs. For the minimum weight total domination problem, a variable neighborhood search approach is proposed, with carefully designed mechanisms for shaking, local search, and fitness function evaluation. The results show that the proposed algorithm achieves optimal solutions on small and medium instances and outperforms competing approaches on large graphs. Additionally, an application of this problem for accelerating information spreading in social networks is proposed. For the minimum weight independent domination problem, two new integer linear pro- gramming models are developed. Solving these models finds optimal solutions for all smaller instances while demonstrating superior performance compared to competing exact approaches on larger graphs. In addition, a greedy heuristic is proposed that outperforms competing greedy methods on most instances. In the case of k-strong Roman domination, a greedy heuristic based on node coverage information is developed, along with a metaheuristic approach based on variable neighborhood search that uses the greedy algorithm for initialization. This problem is particularly challenging due to the exponential complexity of solution feasibility verification, leading to the introduction of the concept of quasi-feasibility that enables efficient feasibility assessment during the search. Experimental results show that the proposed algorithm consistently outperforms the greedy approach and existing competing methods, especially on larger graphs. The practical value of the algorithm is illustrated through a case study involving the optimal positioning of fire stations and vehicles in urban municipalities to ensure the entire city is safe in the event of k simultaneous fires. For the minimum domination problem, a new hybrid approach called IRIS is proposed. IRIS is designed as a general-purpose framework that bridges the gap between exact integer linear programming solvers and heuristic search by iteratively fixing selected variables to reduce the search space. Тhe novelty lies in its flexible subproblem construction mechanism, which can be tailored using various selection strategies. In this study, we implement and evaluate a specific configuration of IRIS that utilizes historical statistical data and a node-coverage-based heuristic to intelligently identify variables for fixing. This targeted approach allows the ILP solver to find high-quality solutions for large-scale instances that are computationally prohibitive for exact methods. Experimental results demonstrate that IRIS achieves competitive performance com- pared to the best existing methods, establishing it as a valid alternative for solving domination and potentially other NP-hard problems. URI: http://hdl.handle.net/123456789/5782 Files in this item: 1
phdStefanKapunac.pdf ( 3.299Mb ) -
Rizvanolli, Fuat (Belgrade , 1982)[more][less]
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Kordić, Stevan (Beograd , 2016)[more][less]
Abstract: Constrain satisfaction problems including the optimisation problems are among the most important problems of discrete mathematics with wide area of application in mathematics itself and in the applied mathematics. Dissertation study optimisation problem and presents an original method for finding its exact solution. The name of the method is Sedimentation Algorithm, which is introduced together with two heuristics. It belongs to the class of branch-and-bound algorithms, which uses backtracking and forward checking techniques. The Sedimentation Algorithm is proven to be totally correct. Ability of the Sedimentation Algorithm to solve different type of problems is demonstrated in dissertation by its application on the Boolean satisfiability problems, the Whitehead Minimisation Problem and the Berth Allocation Problem in container port. The best results are obtained for Berth Allocation Problem, because its modelling for Sedimentation Algorithm includes all available optimisation techniques of the method. The precise complexity estimation of the Sedimentation Algorithm for the Berth Allocation Problem is established. Experimental results verify that the Sedimentation Algorithm is capable to solve the Berth Allocation Problem on the state of art level. URI: http://hdl.handle.net/123456789/4413 Files in this item: 1
StevanKordic.pdf ( 2.477Mb ) -
Kapetanović, Miodrag (Belgrade)[more][less]
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Cvetković, Predrag (Belgrade , 1976)[more][less]
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Arbutina, Bojan (Faculty of Mathematics, University of Belgrade , 2009)[more][less]
Abstract: The main research topic of this dissertation are extreme mass ratio contact close binary systems, q 0.1, of W Ursae Majoris (W UMa) type. These close binaries (CBs) represent an interesting class of objects in which ”normal”, approximately one solar mass main-sequence star is in contact with a significantly less massive companion, M2 ∼ 0.1 M . Earlier theoretical investigations of these systems found that there is a minimum mass ratio qmin = M2/M1 ≈ 0.085 − 0.095 (obtained for n = 3 polytrope - fully radiative primary) above which these CBs are stable and could be observed. If the mass ratio is lower than qmin, or, equivalently, if orbital angular momentum is only about three times larger than the spin angular momentum of a massive primary, a tidal instability develops (Darwin’s instability) forcing eventually the stars to merge into a single, rapidly rotating object (such as FK Com-type stars or blue stragglers). However, there appear to be some W UMa-type CBs with empirically obtained values for the mass ratio below the theoretical limit for stability. The aim of this dissertation is to try to resolve the discrepancy between theory and observations by considering rotating polytropes. By including in theory the effects of higher central condensation due to rotation we were able to reduce qmin to the new theoretical value qmin = 0.070 − 0.074, for the overcontact degree f = 0 − 1, which is more consistent with the observed population. Other candidate systems for stellar mergers such as AM CVn-type stars have also been discussed in the dissertation. URI: http://hdl.handle.net/123456789/716 Files in this item: 1
phdBojanArbutina.pdf ( 6.326Mb ) -
Ćelić, Momir (Banjaluka , 1986)[more][less]
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Šošić, Milena (Beograd , 2025)[more][less]
Abstract: Conversational text messages represent an important form of digital communication in modern society. With the development of information technologies, various communication tools have emerged, such as email, social media, instant messaging tools, and automated response systems. Messages generated within these tools, unlike standard texts, have a specific structure that allows for the classification of individual messages or sets of messages that form a conversation. Classification labels are defined by the specific task being addressed and can be either single-label or multi-label, which enables the recognition of complex interrelationships between the categories. Introducing moral and emotional dimensions of language into research is crucial for understanding the complex patterns of human communication, particularly in the context of digital platforms and social media. Machine learning (ML) methods, such as deep neural networks (DNN), facilitate the utilization and more precise recognition of these aspects while simultaneously providing an efficient way to classify emotions and moral values expressed in texts. The noticeable complexity in the expression of human emotions and moral values, which are often conveyed implicitly and depend heavily on context, makes their recognition particularly challenging. One of the major challenges is the lack of or limited availability of resources in terms of size and diversity for low-resource languages, including Serbian. The development of linguistic resources, such as annotated lexicons and corpora, plays a crucial role in this process by providing the necessary knowledge sources for building and improving existing ML models. Linguistic resources enable models to learn how different emotional expressions and moral values influence the tone and meaning of communication. To support this, a semantic lexicon for sentiment intensity, SentiWords.SR, containing approximately 15k words, was developed for the Serbian language, along with the associated tool SRPOL for measuring sentiment intensity in textual sequences in Serbian. Additionally, a semantic lexicon for emotional affect, EmoLex.SR, comprising around 9.8k words with assigned emotional intensity values, and a semantic lexicon for moral values, MFD.SR, consisting of approximately 4.3k words with associated moral value weights, were developed. Significant efforts were also made in annotating the first conversational corpora from social media with emotional and moral categories. In this regard, the Social-Emo.SR corpus (∼34.6k messages) was developed, consisting of the Twitter-Emo.SR subcorpus (∼16.7k messages) and the Reddit-Emo.SR subcorpus (∼17.9k messages), collected from Twitter and Reddit, respectively. Furthermore, by searching for key moral-related terms, a subset of messages expressing potential moral stances was extracted from Social-Emo.SR. This subset, named Social-Mor.SR (∼13.6k messages), was manually verified and annotated by human annotators and consists of the Twitter-Mor.SR subcorpus (∼6.1k Twitter messages) and the Reddit-Mor.SR subcorpus (∼7.5k Reddit messages). In the context of DNN architectures, models based on recurrent networks or transformers, trained on these resources, enable the recognition and utilization of emotional and moral aspects of language in various contexts. The combination of advanced algorithms, such as Bidirectional Long Short-Term Memory (BiLSTM) networks and the attention mechanism with linguistically and culturally adapted resources (Meta) opens new possibilities for analyzing moral and emotional aspects of language. This has broad applications in classification tasks such as recognizing personal context, truthfulness of posts, or types of engagement in digital communication. For personal context recognition, i.e. classifying corporate emails as either business-related or personal, results show that using a carefully designed hybrid approach (BiLSTM-Att+Meta) across entire conversation branches yields the best results, comparable to published benchmarks on the same task. In experiments related to rumor veracity classification and identifying engagement types in response to rumors, it was demonstrated that moral and emotional attributes derived from semantic lexicons (EmoAttr, MorAttr ⊆ Meta) improve classification accuracy by +4.2% and +3.8% respectively, compared to methods without these attributes. For emotion recognition in Serbian conversational texts, experiments revealed that transformer-based models fine-tuned on the task achieved F1-scores of approximately 53%, reaching performance levels reported for multi-label classification on the same emotional category set. Additionally, experiments showed that further data preprocessing and balancing improved model performance. In moral value and moral sentiment classification tasks, using the Social-Mor.SR corpus and its subcorpora, an F1-score of ∼46% was achieved for moral value recognition and ∼38% for moral sentiment recognition, indicating acceptable results but also the need for further model optimization. Fine-tuning LLaMA models yielded reasonable but slightly lower performance compared to BERT-based architectures. Since model performance is directly dependent on the data they are trained on, there is potential for further improvements by refining and balancing initial annotations in the utilized corpora. URI: http://hdl.handle.net/123456789/5774 Files in this item: 1
Doktorski_rad_Milena_Sosic.pdf ( 6.206Mb )