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1.
Building a Brand: A Multimodal Analysis of the Brand I Feel Slovenia
Ema Ivanuša, 2021, master's thesis

Abstract: This master’s thesis aims to analyse how the brand I Feel Slovenia uses verbal and visual texts to present its brand identity to the audience on its official website. Specifically, it aims to investigate how this brand uses multimodal texts to convey its core values (“Slovenian green”, “pleasant excitement” and “the elemental”); how it builds a relationship with its audience; and how verbal and visual texts contribute to the overall meaning-making in the presentation of the brand. The study uses multimodal discourse analysis to analyse five multimodal texts, which consist of verbal texts and visual texts, taken from the official website of the brand I Feel Slovenia. Both verbal and visual texts were analysed in terms of register variables (field, tenor and mode) and their intermodal connections. The analysis has shown that both verbal and visual texts convey the core values of the brand differently but are equally important in their presentation. Both types of texts build a positive relationship with the audience through the use friendly-neutral language, positive aesthetic appreciation of nature and bright, saturated colours. Both verbal and visual texts are important in the meaning-making in the presentation of the brand, although the latter draw more attention to themselves due to their size and are thus the dominant components.
Keywords: branding, brand I Feel Slovenia, multimodal discourse analysis, register variables
Published: 27.07.2021; Views: 150; Downloads: 19
.pdf Full text (1,38 MB)

2.
Shakespeare’s Lady Macbeth and Leskov’s Sergei from Lady Macbeth of Mtsensk: A Stylistic Comparison of Two Accomplices
Nina Gracej, 2020, master's thesis

Abstract: This Master’s Thesis is based on a stylistic analysis and comparison of Shakespeare’s Macbeth and Nikolai Semyonovich Leskov’s Lady Macbeth of Mtsensk, in particular the two accomplices and their direct speech. Shakespeare's Macbeth is a well-known tragedy with five homicides committed in fight for the throne. Leskov's Lady Macbeth of Mtsensk is a lesser-known Russian novel, in which an oppressed wife Katerina and her lover commit a series of crimes to achieve their goals. These works feature four protagonists: Macbeth and Katerina, and their partners and accomplices Lady Macbeth and Sergei. Because of the latter two, the plots lead the heroes to their bitter ends. Even though these works do not seem to have much in common, further analysis shows various parallels and shared elements. Shakespeare’s Macbeth is a dramatic tragedy, while Lady Macbeth of Mtsensk is a novel. Even though Aristotle (1959, 8) claims that tragedy is intrinsically connected with the dramatic genre, we were able to determine that this novel contains numerous elements of tragedy and can be analyzed as a tragedy. Furthermore, we discovered many parallels between the two: both follow the life of the protagonist, who each have one accomplice (i.e., Lady Macbeth and Sergei). They all desire a better life, and in order to achieve their dreams, they are willing to commit crimes. They all make fatal mistakes and are doomed to fail. In both texts, four murders take place. Our goal was to determine if the crucial murders are more thoroughly presented than the others. Then we analyzed the direct speech (figures of speech) of Sergei and Lady Macbeth in some crucial moments: when manipulating their loved ones and towards the end, when desperation and aggression strike out. When manipulating their partners, they mostly use echphonesis, repetition, antonomasia, sarcasm and antithesis. Towards the end, they become aggressive and anxious. They mostly use erotemas, ecphonesis, antonomasia, irony and sarcasm.
Keywords: William Shakespeare, Nikolai Semyonovich Leskov, Macbeth, Lady Macbeth of Mtsensk, stylistic analysis
Published: 21.01.2021; Views: 145; Downloads: 28
.pdf Full text (1,13 MB)

3.
Simulation-based Evaluation of Frequency Response Analysis as a Diagnostic Tool for Deformations of Windings in Power Transformers
Ivan Papa, 2020, master's thesis

Abstract: In this master’s thesis, we have established a model of a transformer winding. This model is based on the multi transmission line theory that allows us to model each turn of the winding separately. By using that approach, it was possible to calculate the frequency response of a winding in the required frequency range from 20 Hz to 2 MHz. The purpose of this simulation was to evaluate the frequency response analysis as a diagnostic tool for deformations of windings in power transformers. An evaluation was performed using sensitivity analysis of several parameters that indicate winding deformations. Finally, axial bending deformation was simulated and successfully diagnosed by applying the frequency response analysis.
Keywords: Power transformer, Frequency response analysis, Diagnostics, MTL model
Published: 03.11.2020; Views: 132; Downloads: 25
.pdf Full text (2,64 MB)

4.
Language of Appraisal in Book Reviews: A Case Study
Katja Časar, 2020, master's thesis

Abstract: This master’s thesis presents an analysis of appraisal in the case of ten book reviews. Their selection is based on several criteria that make them representative of this text type. The selected texts evaluate novels, novellas and short stories that were ranked top 300 according to the Open Syllabus Project 2.0 online data base. This means that they fall into the category of the most often assigned books in educational institutions. The authors of the selected texts are editors, journalists and writers, and there is an even number of male and female reviewers. The purpose of the study is the appraisal analysis of the contemporary English language; therefore, only the recently published texts were selected. The main methodology used in this master’s thesis is the appraisal theory developed by James Martin and Peter White (Martin and White). This theory evolved in the systemic functional linguistics, and it relies on the theoretical concepts of Michael Halliday (Halliday). The appraisal analysis was conducted with help of the analytical tool Catma 5.0, which enables annotation of texts, their analysis and the visualization of data. The results of the research show that the most frequently used attitudinal resources are the expressions of appreciation. Therefore, the evaluation of the story and everything associated with it is in the foreground of the book reviews. The analysis of the selected texts reveals that evaluation is mostly explicit, meaning that the reader is directly invited to engage with the book. The findings indicate that the attitudinal resources are graded more according to intensity and quantity and less according to prototypicality and marginality. This conclusion draws attention to the variety of lexical and grammatical structures in the selected texts that are assumed to be characteristic of this text type in general. The results also show that the reviewers do not include many external sources into the text, which consequently narrows down the dialogistic space and excludes alternative views and attitudes. The appraisal analysis points toward the text-structural and semantic characteristics of book reviews in general. The structure of the selected texts consists of the following elements: information about the author and the book, the plot summary and evaluation of these elements, which are often intertwined. Some reviews also include personal accounts, book details and/or numeric ratings. The most significant semantic characteristic of evaluation expressed in the selected book reviews is the critique of the Western oppressor. The reviewers judge crimes against humanity and question Western perspectives. They also imply the complicity of the readers because they are viewed as members of the Western identity. Additionally, the results of the analysis show that the book reviews are contextual and intertextual text types, which include various means for the realization of appraisal. A vast spectrum of lexical and grammatical structures makes book reviews an interesting research topic with many possibilities for further research.
Keywords: evaluative language, systemic functional linguistics, appraisal theory, appraisal analysis, book review.
Published: 23.07.2020; Views: 325; Downloads: 81
.pdf Full text (2,65 MB)

5.
Effectiveness of proactive password checker based on Markov models
Viktor Taneski, 2019, doctoral dissertation

Abstract: In this doctoral dissertation we focus on the most common method of authentication, the username-password combination. The reason for the frequent use of this authentication mechanism is its simplicity and low cost of implementation. Although passwords are so useful, they have many problems. Morris and Thompson, for the first time almost four decades ago, found that textual passwords were a weak security point of information systems. They have come to the conclusion that users are one of the biggest threats to information system’s security. Since then, we face these problems on a daily basis. Users do not perform the behaviours they need to be done in order to stay safe and secure, although they are aware of the security issues. Because this is a research area that security experts have been dealing with for a long time, in this dissertation we wanted to identify problems related to textual passwords and possible suggested solutions. For this purpose, we first performed a systematic literature review on textual passwords and their security. In doing so, we wanted to evaluate the current status of passwords in terms of their strength, ways of managing passwords, and whether users are still the “weakest link”. We found that one of the less researched solutions is proactive password checking. A proactive password checker could filter out the passwords that are easy-to-guess and only let through the passwords that are harder to guess. In order for a proactive password checking to be more effective, it is necessary for the checker to be able to check the probability that a certain password will be selected by the user. For this purpose, the better password checkers usually use certain tools to calculate password probability i.e., password strength. To find out which method is most suitable for calculating password strength, we have looked at similar solutions throughout history. We have found that Markov models are one of the most common methods used for password strength estimation, although we may encounter some problems when using them, such as sparsity and over-fitting. By reviewing similar solutions, we found that Markov models are mostly trained on only one dataset. This could limit the performance of the model in terms of correctly identifying bad or very strong passwords. As training datasets are important in the development of Markov models, it is clear that they will have some effect in the final assessment of the password’s strength. What we explore in our dissertation, is the importance of this effect on the final password strength estimation. Mainly, we focus on exploring the effect of different but similar datasets on password strength estimation. For the purposes of our study, we analysed publicly available sets of “common passwords” and processed them regarding the frequency distribution of the letters contained in these passwords. We built different Markov models based on these datasets and frequency distribution. This helped us determine if one Markov model was sufficient or if several models were needed to effectively estimate password strength for a wide range of passwords. The results showed statistical differences between the models. In more detail, we found that: - different Markov models (trained on different databases) showed statistically different results when tested on the same dataset, - more diverse datasets are needed to be able to calculate the strength of as many passwords as possible, since one “universal” model, trained on one “universal” dataset is less effective at classifying passwords in different categories (i.e., weak, medium, strong), - different Markov models of 1st and 2nd order, in most cases, give no statistically different outputs, - overall, Markov models can be used as a basis for constructing a more effective password checker that uses multiple different and specific Markov models, which could be more effective if we want to cover a wider range of passwords.
Keywords: passwords, password analysis, password security, password problems, password strength, systematic literature review, Markov models
Published: 13.01.2020; Views: 622; Downloads: 64
.pdf Full text (1,12 MB)

6.
References to American Culture in the TV Series Supernatural: Analysis of Selected Episodes
Sabina Bedek, 2019, master's thesis

Abstract: The main aim of this master's thesis is to look into the use of references to American culture in the selected episodes of TV series Supernatural. The empirical part is divided into two parts. In the first part, there is an analysis of references in the selected episodes, which includes the context in which they appear, explanation and possible understanding or misunderstanding by the Slovene viewers. The analysis shows that most of the references are connected to popular culture, especially TV, movies and music. Other cultural categories which appear are literature, general American culture and sport. The purpose of the most references is to appeal to the broader audience, set the humoristic mood and identify the character. The second part of the empirical part is questionnaire analysis. Questionnaires were handed out to first- and third-year students of English Language and Literature on Faculty of Arts in Maribor. With this questionnaire, the level of understanding of selected references and possible differences between the results of first-year and third-year students have been be examined. The questionnaire contained 10 multiple-choice questions. The results show no significant deviances in the correctness of the answers of third- and first-year students; however, the first-year students reached slightly higher percent of correct answers. The students performed better on questions related to present American popular culture (Hulk, Star Wars, The Parent Trap). Questions with the least correct answers were those on American general culture, especially cultural items that are not present in the Slovene culture (for example, GED and historic cultural elements).
Keywords: popular culture, cultural references, Supernatural, reference analysis, questionnaire analysis
Published: 23.10.2019; Views: 473; Downloads: 116
.pdf Full text (1,62 MB)

7.
Vpliv nizkocenovnih letalskih prevoznikov na ekonomske kazalnike regij severnega jadrana
Marin Kajba, 2019, master's thesis/paper

Abstract: Magistrska naloga proučuje vpliv nizkocenovnih prevoznikov na ekonomske kazalnike regij severnega jadrana. Raziskavo smo opravili na podatkih 12 letališč v Sloveniji, Hrvaški in Italiji. Raziskava je doprinos k znanosti, saj v literaturi nismo zasledili tovrstne raziskave na tem geografskem področju. Tuji avtorji navajajo, da se je s prihodom nizkocenovnih letalskih prevoznikov v odročne kraje spremenil socialno-ekonomski status v regijah. Da bi analizirali vpliv v naši okolici, smo z DEA analizo izračunali tri različne učinkovitosti izbranih letališč (učinkovitost glede števila potnikov, tehnična učinkovitost in splošna učinkovitost). Izračunani so nam pomagali v nadaljevanju, ko smo preverili, kako letališča vplivajo na svojo okolico. Poiskali smo njihove vrednosti korelacije z bruto domačim proizvodom in številom nočitev v regijah. Ugotovili smo, da je večina italijanskih letališč 100% učinkovita v vseh letih, ki smo jih analizirali, učinkovitost ostalih pa narašča skozi leta. Izstopa le domače letališče Jožeta Pučnika, ki mu splošna učinkovitost pada. Rezultati, ki so predstavljeni na koncu dela lahko letališčem pomagajo pri načrtovanju nadaljnjega dela.
Keywords: nizkocenovni letalski prevozniki, Data Envelopment Analysis (DEA), učinkovitost, letališča
Published: 11.06.2019; Views: 568; Downloads: 45
.pdf Full text (3,02 MB)

8.
FORMULATION, PREPARATION AND CHARACTERIZATION OF NANOEMULSIONS FOR PARENTERAL NUTRITION
Dušica Mirković, 2019, doctoral dissertation

Abstract: The aim of this doctoral research was to develop and optimize parenteral nanoemulsions as well as the total parenteral nutrition (TPN) admixture containing a nanoemulsion obtained in the course of the optimization process (hereinafter referred to as optimal nanoemulsion), and to examine their physicochemical and biological quality as well. In addition, the quality of the prepared nanoemulsions was compared with the quality of the industrial nanoemulsion (Lipofundin® MCT/LCT 20%), and, in the end, the TPN admixture initially prepared was also compared with the admixture into which the industrial emulsion was incorporated. Parenteral nanoemulsions that were considered in this dissertation were prepared by the high-pressure homogenization method. This method is the most widely applied method for the production of nanoemulsions due to the shortest length of homogenization time, the best-obtained homogeneity of the product and the smallest droplet diameter. For the nanoemulsion formulation, preparation and optimization purposes, by using, firstly, the concept of the computer-generated fractional design, and, after that, the full experimental design, the assessment of both direct effects of different formulation and process parameters (the oil phase type, the emulsifier type and concentration, a number of homogenization cycles and the pressure under which homogenization was carried out) as well as the effects of their interactions on the characteristics of prepared nanoemulsions was performed. Monitoring the nanoemulsion physical and chemical stability parameters was carried out immediately after their preparation, and then after 10, 30 and 60 days. It included the visual inspection, the measurement of the droplet diameter (the mean and volume droplet diameter), the polydispersity index, the ζ-potential, the pH value, the electrical conductivity, and the peroxide number. After the preparation and after 60 days, the biological evaluation (the sterility test and the endotoxic test) of the prepared nanoemulsions was carried out. As far as the characterization of the TPN admixture is concerned, it included practically the same parameters. The dynamics of monitoring the characteristics of the TPN admixture was determined on the basis of practical needs of hospitalized patients (0h, 24h and 72h). The scope and comprehensiveness of this issue indicated the need to divide the doctoral dissertation into three basic stages. The first stage was preliminary. Using the 24-1 fractional factorial design, nanoemulsions for the parenteral nutrition were prepared. They contained either a combination of soybean and fish oil, or a combination of medium chain triglycerides and fish oil. In addition, the type and the amount of an emulsifier used, a number of high-pressure homogenization cycles, and the homogenization pressure, were also varied. The measurement of the above-mentioned parameters for the industrial nanoemulsion was parallely carried out (Lipofundin® MCT/LCT 20%). The objective of this part of the research was to identify critical numerical factors having the most significant effect on the characteristics that define the prepared parenteral nanoemulsions. Parameters that were singled out as the result of this stage of the research (the emulsifier concentration and a number of homogenization cycles) were used as independent variables in the second stage of the research.
Keywords: nanoemulsions, total parenteral nutrition admixtures, high pressure homogenization, design of experiments, optimization, analysis of variance, artificial neural networks
Published: 07.06.2019; Views: 10887; Downloads: 0
.pdf Full text (2,82 MB)

9.
10.
Evaluation of Machine Learning Algorithms for Predicting the Processing Time of Order Picking in a Warehouse
Tilen Škrinjar, 2019, master's thesis

Abstract: Optimization of warehouse processes increases efficiency and lowers the cost of managing a warehouse. The most expensive and time-consuming activity is picking. Knowing picking process time is an important factor for proper organization of material and information flow. Orders delivered to a packing station too early or too late can cause delays in a warehouse. The purpose of this study is to evaluate machine learning pipeline for processing time prediction of order picking. This includes data gathering, data preprocessing and the evaluation of machine learning algorithms, which are the most important aspects of this research.
Keywords: warehouse, order picking, machine learning, regression analysis
Published: 25.02.2019; Views: 671; Downloads: 0

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