MENVSC / Department of Geography and Geo-Information Sciences / Climate change has a crucial impact on livelihoods, economy, and water resources due to the occurrence of weather and climate extreme events such as floods, droughts and heat waves. Extreme weather has been increasing worldwide, hence the need to understand their nature and trends. The aim of this study was to analyse the spatial variability and long-term trends of climate extremes over the Limpopo in South Africa from 1960 to 2014. Rainfall, temperature, and circulation fields were analysed to understand the extent, nature of climate extremes over the Limpopo. Extreme value theory (EVT) is a powerful method that was also employed in this study to provide statistical models for events rarely observed. R statistical software was used for clustering analysis which has a variety of functions for cluster analysis. Any station whose value is larger than 95th for any day of the season was considered as a widespread extreme event. The results show that the study area is highly vulnerable to extreme events due to its latitudinal location and low altitude. Anomalous cut-off lows, tropical cyclones and tropical storms are the major extreme producing systems affecting the Limpopo province whilst the Botswana High becomes dominant during heat waves and drought. Extreme weather events are common in Limpopo during summertime and often coincide with mature phases of the El Nino Southern Oscillation. In this study, after the suitable model for data was chosen, the interest was in deriving return levels of extreme maximum rainfall. The computed data for return levels predicted that the 5-year return period’s return level is approximately 223.89 mm, which suggests that rainfall of 223.89 mm or more per month should occur at that station or location on the average of once every five years. / NRF / http://hdl.handle.net/11602/1485

L’émergence récente de grands réseaux, surtout réseaux sociaux en ligne (OSN), a révélé la difficulté de crawler le réseau complet et a déclenché le développement de nouvelles techniques distribuées. Dans cette thèse, nous concevons et analysons des algorithmes basés sur les marches aléatoires et la diffusion pour l'échantillonnage, l'estimation et l'inférence des fonctions des réseaux. La thèse commence par le problème classique de trouver les valeurs propres dominants et leurs vecteurs propres de matrices de graphe symétriques, comme la matrice Laplacienne de graphes non orientés. En utilisant le fait que le spectre est associé à une équation de type différentiel Schrödinger, nous développons des techniques évolutives à l’aide de la diffusion sur le graphe. Ensuite, nous considérons l’échantillonnage des fonctions de réseau (comme somme et moyenne) en utilisant les marches aléatoires sur le graphe. Afin d'éviter le temps «burn-in» de marche aléatoire, avec l'idée de régénération à un nœud fixe, nous développons un estimateur de la fonction de somme qui est non asymptotiquement non-biaisé et dérivons une approximation à la postérieure Bayésienne. La dernière partie de la thèse étudie l'application de la théorie des valeurs extrêmes pour faire une inférence sur les événements extrêmes à partir des échantillons stationnaires des différentes marches aléatoires pour l’échantillonnage de réseau / The recent emergence of large networks, mainly due to the rise of online social networks, brought out the difficulty to gather a complete picture of a network and it prompted the development of new distributed techniques. In this thesis, we design and analyze algorithms based on random walks and diffusion for sampling, estimation and inference of the network functions, and for approximating the spectrum of graph matrices. The thesis starts with the classical problem of finding the dominant eigenvalues and the eigenvectors of symmetric graph matrices like Laplacian of undirected graphs. Using the fact that the eigenspectrum is associated with a Schrödinger-type differential equation, we develop scalable techniques with diffusion over the graph and with gossiping algorithms. They are also adaptable to a simple algorithm based on quantum computing. Next, we consider sampling and estimation of network functions (sum and average) using random walks on graph. In order to avoid the burn-in time of random walks, with the idea of regeneration at its revisits to a fixed node, we develop an estimator for the aggregate function which is non-asymptotically unbiased and derive an approximation to its Bayesian posterior. An estimator based on reinforcement learning is also developed making use of regeneration. The final part of the thesis deals with the use of extreme value theory to make inference from the stationary samples of the random walks. Extremal events such as first hitting time of a large degree node, order statistics and mean cluster size are well captured in the parameter “extremal index”. We theoretically study and estimate extremal index of different random walk sampling techniques

IN ENGLISH Ralph B. Perry's general theory of value was the most extensive and influential axiological project undertaken in the USA prior to WWII. While Perry's main goal is to provide a general definition of value and to describe the means of its criticism, the project also deals with the nature of special values, including aesthetic value. This dissertation thesis traces the aesthetic vein in Perry's theory, which is concentrated on the terms of aesthetic interest and its passive correlate, the aesthetic object. These are also the centerpieces of the definition of aesthetic value. First, interest and its object are defined in their general sense; next, they are defined in their specific aesthetic sense. Perry defines aesthetic interest as the interest in apprehension, and the object of this interest as a problematic intentional object with an index-predicate structure: its index is the localizable source of stimulus, and its predicate, the reflected act of apprehension. The final chapter is devoted to the forms of interplay between aesthetic interest and other interests, and the criticism of aesthetic interest from the aesthetic and moral standpoint. In Perry's theory, the aesthetic value belongs among the trinity of universal values. It is considered autonomous as long as the aesthetic interest...

The aim of this master’s thesis is to examine and analyze the news valuetheory and framing of news regarding child sexual abuse. The researchquestions for this study were:What changes can be found in the use of evocative language in crimejournalism regarding cases of sexual abuse towards children?Are there any clear differences in the language used when investigating theperspectives of objective, sensational and local journalism?The study has been conducted via a quantitative analysis, analyzing 1460articles, from three different newspapers archives. From 1994 up until 2020.The newspapers in the analysis are three Swedish newspapers, Aftonbladet,Dagens Nyheter and Barometern. To arrive at my conclusion, I measured thefrequency of a selected group of evocative words, measuring across the threenewspapers how often the words occurred as well as during what timeperiods.Through the analysis I found that Swedish newspapers, no matter theirdirection towards sensationalism, kept a neutral and objective tone regardingchild sexual abuse in most cases. With not so many cases of purely evocativewords.

Juraj Bodík Abstract This thesis is dealing with the following problem: Let us have two stationary time series with heavy- tailed marginal distributions. We want to detect whether they have a causal relation, i.e. if a change in one of them causes a change in the other. The question of distinguishing between causality and correlation is essential in many different science fields. Usual methods for causality detection are not well suited if the causal mechanisms only manifest themselves in extremes. In this thesis, we propose a new method that can help us in such a nontraditional case distinguish between correlation and causality. We define the so-called causal tail coefficient for time series, which, under some assumptions, correctly detects the asymmetrical causal relations between different time series. We will rigorously prove this claim, and we also propose a method on how to statistically estimate the causal tail coefficient from a finite number of data. The advantage is that this method works even if nonlinear relations and common ancestors are present. Moreover, we will mention how our method can help detect a time delay between the two time series. We will show how our method performs on some simulations. Finally, we will show on a real dataset how this method works, discussing a cause of...

Denna undersökning syftar till att belysa vad som motiverar gymnasieelever att använda GeoGebra i matematiken. Vidare undersöktes även eventuella skillnader i motivation, både typ och grad, hos gymnasieelever som använder GeoGebra ofta respektive sällan i matematiken. Undersökningen grundar sig i motivationsteori och specifikt förväntan-värde teorin och utfördes med kvantitativa- och kvalitativa metoder. Datainsamlingen skedde med en enkät vilken besvarades av 72 gymnasieelever från fyra skolor i Norrbottens län, Stockholms län och Västra Götalands län. Resultatet från undersökningen visar att gymnasieelever främst motiveras av nytto- och kostnadsvärdet som GeoGebra medför. Med andra ord, att GeoGebra ger dem fördelar i matematiken genom att göra det enklare och mer tidseffektiv att hantera matematikproblem med hjälp av GeoGebra. Vidare så visade även resultatet att gymnasieelever som använder GeoGebra ofta motiverades mer av nyttan som verktyget medförde, än gymnasieelever som använder GeoGebra sällan motiverades av det. / The focus of this research was to enlighten what motivates high school students to make use of GeoGebra in mathematics studies. The research also aimed at finding out if there were any differences in motivation, both type and degree, between high school students who used GeoGebra frequently or rarely in mathematics studies. The study was based on motivational theory and more specific expectancy-value theory and used quantitative- and qualitative methods. The data collection was through a survey in which 72 high school students from four schools in Norrbottens county, Stockholms county and Västra Götalands county participated. The result from this study showed that the main reason why high school students are motivated to use GeoGebra in their mathematics studies is because of the utility and cost value the instrument entails. In other means, high school students use the programme because it's easier and more time efficient to solve mathematical problems with it. The study also showed that high school students who use GeoGebra more frequently in mathematics studies are more motivated by the utility value that the instrument brings, than high school students who only use GeoGebra sometimes were.

>Magister Scientiae - MSc / This study sought to identify and fit the appropriate extreme value distribution to flood data, using the method of maximum likelihood. To examine the uncertainty of the estimated parameters and evaluate the goodness of fit of the model identified. The study revealed that the three parameter Weibull and the generalised extreme value (GEV) distributions fit the data very well. Standard errors for the estimated parameters were calculated from the empirical information matrix. An upper limit to the flood levels followed from the fitted distribution.

No description available.

This study investigates the correlation between Millennial workers' sense of belonging and a company’s Corporate Social Responsibility (CSR) initiatives. Bearing in mind the gap in academic research on the introspective impact CSR has on a company’s employees, this study aims to explore how the Millennial workers at one of the biggest banking and insurance companies operating in Bulgaria understand and relate to companies’ philanthropic endeavours. To do so, this paper has used a theoretical framework, which combines four pillars that interact with and amplify one another. Two of them are empirical and present CSR and the Millennials as a generation. The other two are theoretical with social identity theory (SIT), which explains the sense of belonging innate to the Millennials, and corporate citizenship and shareholder value theory, which represent the polar opposites of what CSR should be about. As such, the thesis probes the hypotheses that, on one hand, if a company engages in genuine CSR initiatives, this will lead to an increased sense of belonging from the Millennial employees. However, on the other hand, if the company engages in greenwashing instead, this will lead to a diminished sense of belonging in the target group.  The findings infer that the Millennial workers at the banking and insurance company have strong opinions favouring their company utilizing genuine CSR practices. In addition, the majority of them have shared that if the company started utilizing CSR as means of greenwashing, this would lead to their overall disappointment and a diminished sense of association with the employer. However, the data has also shown that there might be different reasons for why people are joining CSR initiatives. These findings were produced with the help of mixed-method research combining quantitative survey plus qualitative semi-structured individual and focus group interviews.

This study tested a self-generated utility value intervention aimed at increasing undergraduate statistics students’ motivation and achievement. The intervention was based on Situated Expectancy-Value Theory (Eccles & Wigfield, 2020) and encouraged students to make relevant connections between statistics learning content and their lives, primarily emphasising the content’s usefulness to the student, or utility value. In testing a self-generated utility value intervention within the domain of undergraduate statistics, the study extended research previously conducted in high school and undergraduate sciences (psychology and biology) and replicated Hulleman et al. (2017) which tested the role of frequency of students’ connections between the learning content and their lives in their motivation and achievement. In addition to transferring a self-generated utility value intervention to the domain of statistics, the study’s main contribution was made by investigating the role of connection quality—the quality of utility value connections undergraduate statistics students made between the learning content and their lives in their motivation and achievement. The study used collected data from a blindly randomised longitudinal field experiment conducted with undergraduate business school students from a research-intensive university located in the north-eastern USA. The students were of two differing sections of the same 15-week introductory statistics course. The self-generated utility value intervention consisted of prompts, twice during the semester, which instructed stud¬¬ents to write 2-3 paragraphs in response to. Data collected was comprised of students’ gender, first-generation status, initial/final achievement assessments, pre/post self-reports on motivation (expectancy, cost, intrinsic value, utility value) and connection frequency, and researcher scaled ratings coding on student intervention responses for connection quality. Part I Results from this study suggest that the intervention significantly increased students’ achievement (d = .42)—an approximately 7-percentage point difference between intervention and control group conditions. Furthermore, the intervention was found to be especially effective at increasing at-risk, low initial achievement, students’ motivation (expectancy, d = .54) and achievement (d = .87)—an approximately 14.5-percentage point difference between group conditions. Study results also suggest that the intervention’s impact on at-risk students’ achievement was mediated via motivation increases—through students’ expectancy for success, though, not through students’ utility value. The Part I results were confirmatory of Hulleman et al.’s (2017) findings—the intervention effected students’ achievement, but the pathway of indirect effects traversed through students’ expectancy, not their utility value which Hulleman et al. (2017) and this study both hypothesised it would do instead. Part II Results attempted to explain the intervention’s pathways of effects through expectancy to achievement by creating new measures, connection quality measures. Connection quality measures were constructed to capture students’ utility value more effectively than the self-reported utility value survey measure. This study’s Part II Results suggest that the intervention was found, again, to significantly increase students’ achievement (d = 1.46), but the indirect intervention effects traversed a pathway to affecting students’ achievement, not through their expectancy, but through their utility value (as captured via the newly minted connection quality measures), to their motivation (cost and interest), and then to their achievement. The new connection quality measures, exploratorily, were found to capture students’ utility value more effectively than the self-reported utility value survey measure, enabling the self-generated utility value intervention’s effects on students’ achievement and motivation to be further explained. / Math & Science Education