Digital Elevation Models (DEMs) are fundamental datasets for environmental modelling. They provide the basic data from which terrain indices that represent or influence environmental phenomena are derived, for example slope gradient and hydrological contributing area, and also the source from which specific morphometric features are quantified and characterised, for example mountains and drainage basins. This thesis focuses on the latter, with the aim being to develop an algorithm to characterise the landscape in terms of five morphometric features (peaks, passes, pits, ridges and valleys) and to assess its validity and effectiveness for characterising landform from DEMs. The research in this thesis is divided into two parts. First, an algorithm of morphometric characterisation of landform from OEMs is developed based on a locally fitted quadratic surface and its positional relationship with the analysis window. Five requirements are taken into account within the algorithm: (1) the ideal cases of different morphometric features are simply and clearly defined; (2) the output is spatially continuous to reflect the inherent fuzziness of landform features; (3) the output is easily combined into a multi-scale index across a range of operational scales; (4) the standard general morphometric parameters can be easily quantified due to the easy calculation of first and second order derivatives from the quadratic surface; and (5) the algorithm is applicable to the different data structures used to represent DEMs. An additional benefit of the quadratic surface is the derivation of the R?? goodness-of-fit statistic, which allows both an assessment of the reliability of the results and the complexity of the terrain. Of the five morphometric features identified using the algorithm, valleys are perhaps the most commonly used. Therefore the second part of this thesis is a more detailed comparison between the Multi-Scale Valleyness (MSV) and three existing algorithms (D8, D∞ and MrVBF). D8 and D∞ are global flow accumulation algorithms, and perform well when characterising valley centre lines. However, they do not identify the valley areas themselves, although this is to be expected given their formulation. MrVBF focuses on characterising valley bottoms and so performs well when characterising valleys in broad and topographically flat areas. It does not identify valleys in the steeper upland parts of a catchment, although this too is something to be expected given its formulation. MSV directly characterises valley areas from a geomorphometric point of view, and performs well for both upland and lowland catchments, irrespective of their width. Overall, the results show that the single- and multi-scale terrain indices developed in this research perform well when characterising the five morphometric features. The approach has considerable potential for use in environmental modelling and terrain analysis.

The thesis focuses on the insolvency proceedings, which were performed in the company MSV Metal Studénka, as a traditional Czech manufacturing company, which is engaged in the manufacturing of products for the railway, construction and automotive industries. The company got into insolvency in response to the economic crisis that hit the entire Euro-Atlantic region in 2008. Moreover, in 2008, the new Insolvency Act entered into force, it introduced new options how to solve bankruptcy in the Czech law, including a company reorganization controlled by its creditors. The thesis identifies and analyzes the main steps in the restoration process made by the crisis management, examines whether insolvency could be predicted even before the crisis, and compares the satisfaction of creditor groups in insolvency proceedings with the market average.

The market for decentralised financial instruments, more commonly known as cryptocurrencies, has gained momentum over the past recent years and the application areas are many. Modern portfolio theory has for years demonstrated its applicability to traditional assets, such as equities and other instruments, but to some extent omitted the application of mathematical portfolio theory with respect for cryptocurrencies. This master's thesis aims to evaluate both traditional and DeFi assets from a modern optimization perspective. The focus area includes whichallocation structures that minimize the risk-adjusted return. The optimizations strategies are based on the risk measures, standard deviation, Conditional Value at Risk and First linear partial moment. The method has its structure in different scenarios where the outcome is optimized for traditional assets, DeFi assets and a hybrid set of these. The input data for the optimization methodology is based on weekly and adjusted price data for the assets. The output variables are weight-distribution, risk levels, return, maximum drawdown and graphic visualizations. Our results show that there is a value in incorporating parts of assets from the decentralized financial world in a portfolio provided that the risk-adjusted ratio increases through but through both higher returns and higher potential risk. These results are based on incorporation of certain parts of the new landscape where more established assets such as Bitcoin, Ethereum etc. have proven to perform well while other assets that are less traded shows a significantly worse result relative to risk. / Marknaden för decentraliserade finansiella instrument, mer känt som kryptovalutor, har tagit sin fart de senaste åren och applikationsområdena är många. Modern portföljteori har i åratal visat sin tillämpbarhet på traditionella tillgångar, såsom aktier och andra instrument, men till en viss grad utelämnat applicering av matematisk portföljteori med avseende på kryptovalutor. Denna master uppsats ämnar till att utvärdera både traditionella och DeFi tillgångar ur ett modernt optimerings-perspektiv. Fokusområdet innefattar vilka allokeringsstrukturer som minimerar den risk justerade avkastningen. Optimeringsstrategierna baseras på riskmåtten, standardavvikelse, Conditional Value at Risk samt First linear partial moment. Metodiken har sin grundstruktur i olika scenarion där man studerat optimerade utfall för traditionella tillgångar, DeFi tillgångar samt en hybrid uppsättning av dessa.  Ingångsdatan till optimeringsmetodiken baseras på veckovis och justerad prisdata för tillgångarna. Utgångsvariablerna är allkokeringsfördelning, risknivåer, avkastning, maximum drawdown samt grafiska visualiseringar.  Våra resultat visar att det finns det finns ett värde i att omstrukturera sin portfölj med delar av tillgångar från den decentraliserade finansvärlden under förutsättningarna att riskjusterade kvoten ökar genom men genom både högre avkastning och högre potentiell risk. Dessa resultat bygger på inkorporering av vissa delar av de nya landskapet där mer etablerade tillgångar som Bitcoin, Ethereum etc. har visat sig prestera bra medans andra tillgångar som är mindre omsatta visar ett avsevärt sämre resultat relativt risk.

The level of knowledge and awareness among patients about the concepts and implications of medical radiation is unknown. The purpose of this qualitative, case study was to explore patients' awareness and knowledge of information regarding this topic from their perspectives. The health belief model provided the framework for the study. A total of 20 individuals were recruited using purposive sampling. All participants were above the age of 18 in central North Carolina and had undergone or are currently undergoing medical radiation exams. Data were collected using semistructured interviews and analyzed using Yin's 5-phased cycle, which involved compiling, disassembling, reassembling, interpreting, and concluding. According to study findings, patients were generally aware of the harmful effects and seriousness of medical radiation if uncontrolled. Patients also cited the importance of having the proper information and resources to educate oneself, being more careful with their bodies to avoid examinations with radiation, and hearing reports about individuals getting ill from medical radiation exposure as cues to action that may benefit patients who are about to undergo medical radiation exams. The findings of this study may contribute to positive social change by illustrating ways to improve information dissemination and involvement of patients in understanding medical radiation and its perceived risks. The results of this study may help health practitioners in developing strategies to encourage patients to discuss their medical radiation exposure concerns proactively.

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