The doctoral dissertation studies applications of the methods of qualitative modelling to solve problems associated with external credit ratings. Qualitative modelling is a tool which can solve tasks under shortage of relevant information items. Correlation analysis is used if relevant data sets are available and complement the qualitative analysis. External credit rating assessments are closely related to possibilities of insolvency of business entities and the subsequent bankruptcies. Mutual interlinks of bankruptcy probabilities and qualitative models are presented in details. Two specific models are given. Due to the adopted legislative measures were also tested match of the ratings from a variety of external credit rating agencies using cluster and correlation analysis. The above mentioned results are used to develop a qualitative model of external credit ratings, which is the main outcome of this dissertation. The results of model scenarios of assessment of the influence of regulation external credit rating on the business entity, investors, as well as regulatory authorities are presented in details.

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High speed data from Wide Area Measurement Systems (WAMS) with Phasor Measurement Units (PMU) enables real and non-real time monitoring and control of power systems. The information and communication infrastructure used in WAMS efficiently transports information but introduces cyber security vulnerabilities. Adversaries may exploit such vulnerabilities to create cyber-attacks against the electric power grid. Control centers need to be updated to be resilient not only to well-known power system contingencies but also to cyber-attacks. Therefore, a combined event and intrusion detection systems (EIDS) is required that can provide precise classification for optimal response. This dissertation describes a WAMS cyber-physical power system test bed that was developed to generate datasets and perform cyber-physical power system research related to cyber-physical system vulnerabilities, cyber-attack impact studies, and machine learning algorithms for EIDS. The test bed integrates WAMS components with a Real Time Digital Simulator (RTDS) with hardware in the loop (HIL) and includes various sized power systems with a wide variety of implemented power system and cyber-attack scenarios. This work developed a novel data processing and compression method to address the WAMS big data problem. The State Tracking and Extraction Method (STEM) tracks system states from measurements and creates a compressed sequence of states for each observed scenario. Experiments showed STEM reduces data size significantly without losing key event information in the dataset that is useful to train EIDS and classify events. Two EIDS are proposed and evaluated in this dissertation. Non-Nested Generalized Exemplars (NNGE) is a rule based classifier that creates rules in the form of hyperrectangles to classify events. NNGE uses rule generalization to create a model that has high accuracy and fast classification time. Hoeffding adaptive trees (HAT) is a decision tree classifier and uses incremental learning which is suitable for data stream mining. HAT creates decision trees on the fly from limited number of instances, uses low memory, has fast evaluation time, and adapts to concept changes. The experiments showed NNGE and HAT with STEM make effective EIDS that have high classification accuracy, low false positives, low memory usage, and fast classification times.

In order to achieve Net Zero emissions in the UK by 2050 and decarbonize the energy sector the integration of increased volumes of additional renewable wind energy is critical. Distribution network operators face challenges in increasing the capacity of this variable source of energy onto the electricity networks. Distribution network operators in Scotland have integrated more wind energy onto their networks to date and have learnings through experience that are worth investigating. The research conducted in this thesis is a comparative analysis of the Network Development Plans of three UK distribution Network Operators, Scottish Power Energy Networks in southern Scotland, Scottish and Southern Energy Networks in northern Scotland, and UK Power Networks in the southeast of England area.  The method used is a comparative analysis of the Network Development Plan documents using a set of pre-selected variables while also allowing for other new emergent variables to be included in the analysis and results. The pre-defined variables are grid capacity, flexibility, grid integration technologies, market structures, planning and regulatory framework, operational experience, efficiency, and location / wind availability. Variable codewords were used to perform the document search and related keywords were used where returns were insufficient. Two further variables emerged frequently in the texts as a result of keyword searches which were transmission links and energy storage and were also included in discussions. Results of the research reveal that Scottish Hydro Electricity Power Distribution, who operate in the north of Scotland, and Scottish Power Energy Networks who operate in the south of Scotland, appear to have a more innovative and proactive approach to grid integration technologies, stakeholder engagement, and innovation projects for increased wind energy integration. UK Power Networks have a larger investment plan approved by the UK electricity and gas markets regulator, Ofgem, but lack of experience in integration of large volumes of wind energy leaves it lagging behind its counterparts when it comes to integration and management of wind energy. Findings from analysis of the Network Development Plans is backed up in literature which claim that energy storage, smart grid technologies, and infrastructure upgrades are critical for integration of wind energy to transform it into a reliable and predictable energy source and manage its integration on to the electricity networks.

Food systems are complex social-ecological systems. Currently, they are the source of large-scale health problems and environmental impacts, and there is widespread agreement that transformative change is needed. Scenarios are useful tools for directing such change, as they provide engaging future visions that work well with complex systems.  This thesis is a part of Mistra Food Futures, a platform for a sustainable transformation of the Swedish food system, where scenarios for Swedish food futures are being developed. The thesis purpose is to contribute to the scenario development by the use of systems mapping and semi-quantitative scenario modelling. The thesis builds on four scenario narratives previously developed by Mistra Food Futures researchers. During the thesis process, these scenario narratives were re-interpreted as Causal Loop Diagrams. The diagrams were then used as the basis for constructing a food system model in the form of a Fuzzy Cognitive Map. Simulations were run to investigate the conditions under which the scenarios could be reproduced by modelling. The modelling uncovered several system dynamics: the competition or shared interests of different types of agriculture; the system impacts of novel foods; the vulnerabilities of localised food systems; the importance of food culture; and the interactions of environmental policy with farming systems. Another finding was system attractors where scenarios mix, and these are presented as alternative scenarios. The thesis contributes to the scenario development by making relationships, system feedbacks, and drivers explicit by systems mapping, as well as providing a user-friendly model that can be used for further system exploration. The analysis of specific dynamics can be used to inform upcoming scenario iterations, and alternative scenarios can be used to maintain analytical depth when scenario interactions are discussed. The process also provides a demonstration of the use of Fuzzy Cognitive Maps in scenario modelling.

Previous research has found a correlation between death anxiety and self esteem. Researchers have found that both self-esteem and death anxiety play a significant role in an individual's behavior. The purpose of this study was to investigate a correlation, if any, between death anxiety and self esteem using death related scenarios. It was hypothesized the high death anxiety groups will have lower self-esteem than the low death anxiety group, and that the low self-esteem group will have higher death anxiety than the high self-esteem group. Results of an ANOVA indicate that there is a significant difference between the high death anxiety group and low death anxiety group concerning self-esteem. The results also indicate that there is a significant difference between the low self-esteem group and the high self-esteem group concerning death anxiety. Overall it was found that there was significant negative correlation between death anxiety and self-esteem.

Every year floods are responsible of a significant number of human losses, many of which could be avoided with a broader implementation of flood forecasting systems. Nevertheless, there are still some technological and economic limitations that impede the creation of these systems in many parts of the world. At the core of many flood forecasting systems is a hydrologic model that transforms the weather forecast into a flow forecast. Using real-time modeling for potential floods poses a series of problems: if the model is complex, the computational power required can be significant, and consequently expensive, and if the model is simple enough to run on regular computers in the time allotted, it is likely that the results will not be accurate enough to be useful. I propose the development of a standardized method for using pre-computed scenarios as an alternative to real-time flood modeling. I explain how pre-computing has been used on other realms in the past, and how it is beginning to be implemented in different branches of hydrology, the prediction coastal flooding due to storms or tsunamis being one of the most developed. My research has focused on answering the questions that arise during the design stage of a flood forecasting system not only for rain or snow driven floods, but also by anthropogenic-produced floods. I analyze the number of parameters and their granularity to be used to create the scenarios, the accuracy of the results, different strategies to implement the systems, etc. Finally, I present some test-cases of the application of the method, and assess their results.

In this paper it is investigated the role that geothermal energy could play in theenergy mix, to meet new system requirements. As any other source, geothermal energy harnessing implies a number of risksmainly related to induced seismicity and landslides, together with the releaseof as greenhouse gases and metal salts. Moreover, important barriers to itsimplementation still exist, mainly concerning financial aspects and drillingoperations. As well, administrative status is uncertain and related investmentin R&D negligible. However, geothermal energy presents important advantages in relation toother energy sources, as its reliability and large capacity factor, comparable tonuclear and natural gas plants. It could help to reduce both the globalwarming, whose potential is up to 5 times lower than in the case of fossilfuels, and the landuse, the lowest of any power plant. Additionally, in spite ofthe high and risky initial investment, energy produced by geothermal means is amongst the cheapest. The geothermal potential is large enough to substantially contribute to theenergy mix, through locally available resources. Economic potential in Europeby 2050 is estimated in 100 – 4 000 TWheand 880–1 050 TWhth. Nevertheless, currently available technology strongly limits the access togeothermal resources. In addition, predictions about geothermal utilizationare modest and have hardly been achieved to date. The key for the future isthe development of the Engineered Geothermal Systems.

The creation of futures scenarios is a tool to addresschallenges towards sustainability in planning and thebuilt environment. Scenarios in the project BeyondGDP growth explore futures where priority is givento social and environmental aspects and economicgrowth is regarded as uncertain. When futures areused as an input to planning, there has to be anawareness of the possible consequences of those.Sustainability assessment for futures scenarios aimsto give a comprehensive assessment of how differentscenarios can affect relevant aspects. This thesis gives an overview of current methods forsustainability assessment of futures scenarios. It alsoproposes improvements to one of them and tests iton the Beyond GDP growth scenarios. SAFS (SustainabilityAssessment Framework for Scenarios) isthe method selected. SAFS considers environmentaland social aspects providing qualitative results anduses consumption perspective and life cycle approach. Improvements to SAFS are proposed in two directions.First, the Doughnut developed by Raworth(2012) is integrated in the method. It gives a graphicrepresentation, putting each aspect in context withthe others and facilitate the communication of theassessment results. Second, an alternative approachis suggested to evaluate the consequences of environmentaldeprivation on social conditions. Thisalternative approach can also help communicateuncertainties. / Att skapa framtidsscenarier är ett verktyg för attadressera utmaningar relaterade till hållbarhet inomsamhällsplanering och samhällsbyggnad. ProjektetBortom BNP-tillväxt utforskar i ett antal scenarierolika framtider där sociala och miljömässiga aspekterfår prioritet och ekonomisk tillväxt betraktas somosäker. När framtidsscenarier används som inputi samhällsplanering behöver det finnas en medvetenhetom dessa framtiders möjliga konsekvenser. Hållbarhetsbedömning av framtida scenarier utgören omfattande utvärdering av hur olika scenarier kanförväntas påverka relevanta aspekter. Den här uppsatsen ger en översikt över befintligametoder för hållbarhetsbedömning av framtidsscenarier,den applicerar en av dessa metoder - SAFS(Sustainability Assessment Framework for Scenarios) -på scenarierna inom Bortom BNP-tillväxt och föreslårförbättringar till metoden. SAFS väljs därför att densom metod tar hänsyn till såväl miljö- som socialaaspekter, ger kvalitativa resultat och utvärderar scenariernaur ett konsumtions- och livscykelperspektiv. Två förbättringar av SAFS föreslås. Den ena är attintegrera Raworths “Doughnut” (2012) eftersomden erbjuder ett sätt att grafiskt representera allautvärderade aspekter tillsammans och underlättaratt kommunicera resultatet från bedömningen. Denandra förbättringen innebär ett annat angreppssättför att utvärdera konsekvenserna av miljöförstöringför sociala aspekter. Det föreslagna angreppssättetkan även underlätta att kommunicera metodens inneboendeosäkerheter gällande resultaten. / Beyond GDP growth

The underlying architecture of the Internet has been mostly the same since its beginning in the 1960s and the TCP/IP protocol stack remains ubiquitous. However the Internet is today used for much wider purposes than what was originally intended and now the most common use of the Internet is for the distribution of various forms of content. Information Centric Networking (ICN) is an alternative architecture responding to this change in usage, intended to be more prepared to handle the new requirements of the Internet not only today but also in the future. The primary concern in ICN is the secure and efficient distribution of content. Current ICN research often concerns applications on various disaster scenarios as it is believed that ICN has properties that match the requirements of such scenarios. In this thesis that research is continued by developing an especially designed information retention solution, using the existing ICN implementation of Content Centric Networking (CCN). The aim is to maximisise and prolong the availability of as much content as possible in disaster-stricken networks by preemptively replicating content across the network topology. The solution is then evaluated against a scenario set in a network topology consisting of virtual machines. The final result is that the solution performs satisfactorily and thus demonstrate the potential of ICN when applied to such scenarios. / Internets underliggande arkitektur har varit i stort sett oförändrad sedan sin begynnelse på 1960-talet, och TCP/IP protokollstacken är fortsatt universell. Dock så används Internet idag för betydligt bredare ändamål än de ursprungliga syftena, och nu används Internet främst för att distribuera olika former av innehåll. Information Centric Networking (ICN) är en alternativ arkitektur som svarar på denna förändring i använding, avsedd att vara mer förberedd att hantera de nya kraven på Internet inte bara idag men också i framtiden. Den största angelägenheten i ICN är att distribuera innehåll på ett säkert och effektivt vis. Nuvarande forskning inom ICN handlar ofta om tillämpningar på olika sorters katastrofscenarier då tron är att ICN har egenskaper som motsvarar kraven hos sådana scenarier. I den här uppsatsen fortsätts denna forskning genom att en speciellt formgiven informationsbevaringslösning utvecklas, som nyttjar den existerande ICN-implementationen Content Centric Networking (CCN). Målet är att maximera och förlänga tillgängligheten av så mycket innehåll som möjligt i katastrofdrabbade nätverk genom att i förebyggande syfte replikera innehåll genom nätverkstopologin. Lösningen evalueras sedan mot ett scenario som utspelas i en nätverkstopologi utav virtuella maskiner. Det slutgiltiga resultatet är att lösningen presterar tillfredsställande och på så vis demonstrerar potentialen hos ICN vid tillämpning på sådana scenarion.