The increased usage of solar panels worldwide highlights the importance of being able to detect faults in systems that use these panels. In this project, the historical power output (kWh) from solar panels combined with meteorological data was used to train a machine learning model to predict the expected power output of a given solar panel system. Using the expected power output, a comparison was made between the expected and the actual power output to analyze if the system was exposed to a fault. The result was that when applying the explained method an expected output could be created which closely resembled the actual output of a given solar panel system with some over- and undershooting. Consequentially, when simulating a fault (50% decrease of the power output), it was possible for the system to detect all faults if analyzed over a two-week period. These results show that it is possible to model the predicted output of a solar panel system with a machine learning model (using meteorological data) and use it to evaluate if the system is producing as much power as it should be. Improvements can be made to the system where adding additional meteorological data, increasing the precision of the meteorological data and training the machine learning model on more data are some of the options. / Med en ökande användning av solpaneler runt om i världen ökar även betydelsen av att kunna upptäcka driftstörningar i panelerna. Genom att utnyttja den historiska uteffekten (kWh) från solpaneler samt meteorologisk data används maskininlärningsmodeller för att förutspå den förväntade uteffekten för ett givet solpanelssystem. Den förväntade uteffekten används sedan i en jämförelse med den faktiska uteffekten för att upptäcka om en driftstörning har uppstått i systemet. Resultatet av att använda den här metoden är att en förväntad uteffekt som efterliknar den faktiska uteffekten modelleras. Följaktligen, när ett fel simuleras (50% minskning av uteffekt), så är det möjligt för systemet att hitta alla introducerade fel vid analys över ett tidsspann på två veckor. Dessa resultat visar att det är möjligt att modellera en förväntad uteffekt av ett solpanelssystem med en maskininlärningsmodell och att använda den för att utvärdera om systemet producerar så mycket uteffekt som det bör göra. Systemet kan förbättras på några vis där tilläggandet av fler meteorologiska parametrar, öka precision av den meteorologiska datan och träna maskininlärningsmodellen på mer data är några möjligheter.

A relatively small body of literature in tourism concentrates on lifestyle entrepreneurs in hospitality. Lifestyle entrepreneurs are entrepreneurs that create a business to alter their own lifestyle, interests, and well-being. They are people that are fueled by the desire for adventure and establish a business, usually away from their home country, to generate lifestyle benefits and quality of life. Lifestyle entrepreneurship in tourism is a growing trend and lifestyle entrepreneurs have been praised by previous scholars, for their nongrowth motivation and charismatic characteristics. This research aims to reconsider these entrepreneurs’ motives and values with the purpose of moving beyond their ambitions for themselves, and investigating their motivations and values towards the destination they are located in, and through this explore the role they might play in the development of the destination at large. Using a sample of small guesthouse and hotel owners located in different places around the world, the results show that even though the lifestyle entrepreneurs seem to be primarily motivated by generating well-being for self, the study identifies positive impacts of these entrepreneurs that should not be underestimated and could increase the competitiveness of their destination. The research suggests that promoting these entrepreneurs would contribute to sustainable destination development, considering the small-scale responsible tourism they seem to attract. However, results indicate that they might not be a reliable force for tourism development.

The wind industry is growing rapidly and especially in Europe, offshore wind power has become a serious business with approximately 22 GW installed in 2019. However, for the industry to become even more competitive, costs must be reduced. Especially the Operation and Maintenance (O&M) costs present a challenge to developers and operators. In order to achieve cost savings during the operational phase, the factors influencing the maintenance operations should be identified. This Thesis focuses on the factors influencing the offshore wind turbine foundation maintenance operations. The aim of the Thesis is to identify these factors and their attributes, as well as rank them according to their importance. First, a literature review was conducted to establish the theoretical background for this study. In order to do so, maintenance strategies, offshore wind turbine foundations and the scope of foundation maintenance were described in detail. After that, the factors influencing the maintenance for offshore wind turbine foundations were collected from literature, personal experience, and input from industry experts. Following that, a two-step study with seven industry experts was conducted to validate these factors and their attributes as a first step before then ranking all the attributes by their importance. The experts were asked to rank each attribute by assigning a number from 1-5 where: very high influence (5), high influence (4), medium influence (3), low influence (2) and no influence (1). Since the maintenance differs for the subsea and the above water part of the foundation, the participants had to rank each attribute twice, once for the subsea part and once for the part above water. After the results were analyzed, it can be concluded that the Quality Health Safety Environment (QHSE) was ranked as the most important, followed by technology and standards & guidelines. The environment factor was ranked as the least important before the geographical location and cost factors.

Simultaneously as the societal trends of urbanization, digitalization and electrification of society are moving at a high speed, the Swedish power grid is undergoing a necessary transition to a renewable energy system. Even though there are difficulties on all grid levels, the lack of capacity in some local grids is among the most present problems and originates from the long lead time of grid expansion as well as the challenges within long-term planning of grids. This thesis aims to improve the understanding of future trends’ impact on grid capacity needs. More specifically, a scenario-based and data driven method, with an accompanying model, is derived to target local capacity challenges. The trends identified to pose impact on the future grid capacity were electrification of different sectors, energy efficiency actions, decentralized energy generation, energy storage solutions, flexibility, smart grids, urbanization and climate. The thesis concludes that the impact of a trend on national level is not simply equal to the impact on a local level. Similarly, a long-term increase of the national electricity consumption does not necessarily worsen local capacity challenges. Furthermore, the developed model in this project shows potential to provide more detailed and accurate information about consumption than currently used methods based on standardized power estimations, which could favor more transparent decision making when dimensioning local grids.

How to price your offering is one of the main managerial decision issues today and is alarmingly often not grounded in necessary market and cost research. Pricing is a complex topic, dependent on a multitude of internal and external factors, which makes pricing practice and strategy alignment even more difficult. As a simplifying measure, pricing practices are commonly categorized into three categories: cost-based, competition-based and value-based pricing, of which value-based pricing is considered the superior practice by scholars. Consequently, the issue of how to adopt value-based pricing and how to actually price according to value is pertinent and a main focus of this thesis. What comprises perceived customer value, how a firm creates and captures value, and how a firm chooses to formulate the customer value proposition in order to communicate the generated value are all questions that this thesis investigates and attempts to answer. Furthermore, the effects of the customer-supplier relationship on pricing and change management aspects of a transition to value-based pricing are also investigated and analyzed. In order to answer the research purpose and accompanying research questions, a qualitative single case-study was conducted. The case company was a leading company in the TIC-market, who just recently had started discussing implementing value-based pricing and was therefore deemed as an appropriate case for this study. Empirical data was gathered through semi-structured interviews with the employees as well as the customers of the case company. The analysis of the empirical data in conjunction with the theoretical framework led to a revised analytical model that attempts to explain the relations and correlations of the different concepts discussed in this thesis, as well as conclusions regarding the aforementioned research questions. This study concludes that the common value drivers are Quality, Delivery reliability, Delivery time, Price, Geographical location, Relationship and communication, Customization. Additionally, the study concludes that the alignment of pricing practice and strategy is heavily dependent on internal and external awareness, and it is of utmost importance for a firm engaging in value-based pricing to know not only their customer and market, but also their own capabilities and strengths. Regarding how to formulate the customer value proposition, the study concludes that it should be customized for the specific customer and have a resonating focus with elements of points of difference. Lastly, the study details the challenges that a firm transitioning to a value-based pricing practice might encounter, and the suggestive solutions to these obstacles.

We present a partial implementation of King and Saia 2016’s expected polyno- mial time byzantine agreement algorithm, which which greatly speeds up Bracha’s Byzantine agreement algorithm by introducing a shared coin flip subroutine and a method for detecting adversarially controlled nodes. In addition to implementing the King-Saia algorithm, we detail a new version of the “blackboard” abstraction used to implement the shared coin flip, which improves the subroutine’s resilience from t < n/4 to t < n/3 and leads to an improvement of the resilience of the King-Saia Byzantine agreement algorithm overall. We test the King-Saia algorithm, and detail a series of adversarial attacks against it; we also create a Monte Carlo simulation to further test one particular attack’s level of success at biasing the shared coin flip / Graduate

Habitat loss and climate change are major factors implicated in the decline of bumble bees worldwide. These factors may be particularly acute in regions subject to climatic extremes such as seasonal drought. Combining methods from pollinator research and phylogenetic community ecology, I investigated the impacts of seasonal drought on plant phenology and bumble bee community ecology across gradients of disturbance and soil moisture in a semi-arid ecosystem. Seasonal fluctuations in floral resources coincided with significant phylogenetic clustering in plant communities, with decreasing plant diversity observed under conditions of increasing drought stress. In the late season, modified wet areas supported higher floral resource availability and greater bumble bee abundances as compared to dry woodlands, though wetlands were also an important source of late season floral resources. Despite these local effects, however, the areal extent of natural vs modified matrix habitat accounted for the majority of variation in models explaining bumble bee abundances. Modified matrix habitat was negatively associated, and natural matrix habitat positively associated, with the occurrence of bumble bee workers in June and late-flying queens in July and August. Results provide insight into the temporal niche dynamics of entomophilous flowering plants in this system, and emphasize the importance of conserving natural habitat diversity in efforts to promote resilient plant-pollinator communities. This study also provides evidence for the local extinction of Bombus occidentalis Greene, 1858 and Bombus suckleyi Greene, 1860 from Galiano Island, BC, Canada, as well as the island’s recent colonization by Bombus vosnesenskii Radoszkowski, 1862. / Graduate

We introduce the notion of cellular dg-categories mimicking the properties of topological CW-complexes. We study the properties of such categories and provide various examples corresponding to the well-known geometrical objects. We also show that these categories are suitable for encoding coherence conditions in homotopy theoretical constructs involving A-infinity categories. In particular, we formulate the notion of a homotopy coherent monoid action on an A-infinity category which can be used in constructions involved in Homological Mirror Symmetry.

This dissertation examines the economic, aesthetic, and affective significance of the resurgence of street vendors and their song in Cuba after nearly five decades of silence following the Cuban Revolution of 1959. Their temporary disappearance came hand in hand with the banishment of private modes of labor and entrepreneurship on the island. From colonial times until 1959, street vendors and their songs were a central component of everyday sociality and street economies in Cuba, as well as an integral part of a transnational popular music repertoire. Their recent resurgence overturns prior labor and economic policies in a general context of precarity and accumulated scarcity originating from Cuba’s complex historical position in the global reconstitution of Cold War politics. Since 2010, the Cuban state has sanctioned economic reforms that reintroduce massive forms of self-employment. Significantly, the majority of these can only be exercised through ambulatory vending. As such, the very notions of self-employment, entrepreneurship, and consumption that arise in contemporary Cuba depend, to a large extent, on the mutual circulation of sound and goods. For many self-employed Cubans, no transaction is possible without potential listeners. This research is based on ethnographic fieldwork conducted in Cuba between 2015 and 2019, focusing on questions that emerge in the interaction between vendors, consumers, and the state, as mediated by vocal practices, listening techniques, and the circulation of sound within the particular architectural configuration of Havana. Throughout the dissertation, I develop the term, aural economy, as encompassing the ways in which sound enables modes of exchange as much as sound itself becomes an object of transaction and regulation. I argue that the aural economies arising in contemporary Cuba provide a central way to understand how Cubans negotiate a life worth living under precarious conditions, proposing ways in which to interrogate the unique relationship between aurality and the economy currently reconfiguring the Cuban public sphere. The first chapter examines the aural and racial imaginaries of internal migration from Cuba’s Eastern provinces to the capital, interrogating forms of storytelling that in turn theorize the relationship between notions of song, labor, and dwelling. The second chapter examines the life and labor of a famous peanut vendor in Havana’s old town, interrogating the complex and unequal relationships that unfold between Cuban workers and tourists. The third chapter examines artistic interventions that interrogate the nature of street-vendor songs and approach them as objects of aesthetic experimentation, raising questions about how race, gender, and music hierarchies are linked through questions of labor on the island. The fourth chapter presents a contrastive case study around the aural economy of “el paquete,” an alternative mode of internet consumption in Cuba that circumvents limited access in the island. Taken together, these chapters approach sound as an entry point into the multiple ways in which the mutual relationships between work and life are articulated and contested in contemporary Cuba, linking the affective and the aesthetic with the economic and the infrastructural.

In this dissertation, we adopt the viability approach to mathematical finance developed in the book of Karatzas and Kardaras (2020), and extend it to settings where portfolio choice is constrained. We introduce in Chapter 2 the notions of supermartingale numeraire, supermartingale deflator, and viability. After that, we characterize all supermartingale deflators under conic constraints on portfolio choice. Most importantly, we prove a fundamental theorem for equity market structure and arbitrage theory under such conic constraints, to the effect that the existence of the supermartingale numeraire is equivalent to market viability. Further, and always under the assumption of viability, we establish some additional optimality properties of the supermartingale numeraire. In the end of Chapter 2, we pose and solve a problem of robust maximization of asymptotic growth, under some realistic assumptions. In Chapter 3, we state and prove the Optional Decomposition Theorem under conic constraints. Using this version of the Optional Decomposition Theorem, we deal with the problem, of superhedging contingent claims. In Chapter 4, we consider yet another portfolio optimization problem. Under simultaneous conic constraints on portfolio choice, and drawdown constraints on their generated wealth, we try to maximize the long-term growth rate from investment. Application of the Azema-Yor transform allows us to show that the optimal portfolio for this optimization problem is a simple path transformation of a supermartingale numeraire portfolio. Some asymptotic properties of this portfolio are also discussed in Chapter 4.