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Faculty of Science

 

Recent Submissions

  • Nurmela, Mika (2022)
    We study a system of cold high-density matter consisting purely of quarks and gluons. The mathematical construction of Quantum Chromodynamics (QCD) introduces interactions between the fields, which modify the thermodynamic properties of the system. In the presence of interactions, we can not solve the thermodynamic properties of the system analytically. The method is to expand the result in a series in terms of the QCD coupling constant. This is referred to as the perturbation theory in the context of thermal field theory (TFT). The coupling constant describes the strength of the interaction. We introduce the basic calculation methods used in the QCD and the TFTs in general. We will also include the chemical potential associated with the number of quarks in the system in the calculation. In the case of zero temperature, quarks form a Fermi-sphere such that energy states lower than the chemical potential will be Pauli blocked. The resulting fermionic momentum integrals are modified as a consequence. We can split these integrals into two parts, referred to as the vacuum and matter parts. We can split the calculation of the pressure into two distinct contributions: one from skeleton diagrams and one from ring diagrams. The ring diagrams have unphysical IR divergences that we can not cancel using the counterterms. This is why hard thermal loop (HTL) effective field theory (EFT) is introduced. We will discuss this HTL framework, which requires the computation of the matter part of the gluon polarization tensor, which we will also evaluate in this thesis.
  • Schauman, Julia (2022)
    In this thesis, we explore financial risk measures in the context of heavy-tailed distributions. Heavy-tailed distributions and the different classes of heavy-tailed distributions will be defined mathematically in this thesis but in more general terms, heavy-tailed distributions are distributions that have a tail or tails that are heavier than the exponential distribution. In other words, distributions which have tails that go to zero more slowly than the exponential distribution. Heavy-tailed distributions are much more common than we tend to think and can be observed in everyday situations. Most extreme events, such as large natural phenomena like large floods, are good examples of heavy-tailed phenomena. Nevertheless, we often expect that most phenomena surrounding us are normally distributed. This probably arises from the beauty and effortlessness of the central limit theorem which explains why we can find the normal distribution all around us within natural phenomena. The normal distribution is a light-tailed distribution and essentially it assigns less probability to the extreme events than a heavy-tailed distribution. When we don’t understand heavy tails, we underestimate the probability of extreme events such as large earthquakes, catastrophic financial losses or major insurance claims. Understanding heavy-tailed distributions also plays a key role when measuring financial risks. In finance, risk measuring is important for all market participants and using correct assumptions on the distribution of the phenomena in question ensures good results and appropriate risk management. Value-at-Risk (VaR) and the expected shortfall (ES) are two of the best-known financial risk measures and the focus of this thesis. Both measures deal with the distribution and more specifically the tail of the loss distribution. Value-at-Risk aims at measuring the risk of a loss whereas ES describes the size of a loss exceeding the VaR. Since both risk measures are focused on the tail of the distribution, mistaking a heavy-tailed phenomena for a light-tailed one can lead to drastically wrong conclusions. The mean excess function is an important mathematical concept closely tied to VaR and ES as the expected shortfall is mathematically a mean excess function. When examining the mean excess function in the context of heavy-tails, it presents very interesting features and plays a key role in identifying heavy-tails. This thesis aims at answering the questions of what heavy-tailed distributions are and why are they are so important, especially in the context of risk management and financial risk measures. Chapter 2 of this thesis provides some key definitions for the reader. In Chapter 3, the different classes of heavy-tailed distributions are defined and described. In Chapter 4, the mean excess function and the closely related hazard rate function are presented. In Chapter 5, risk measures are discussed on a general level and Value-at-Risk and expected shortfall are presented. Moreover, the presence of heavy tails in the context of risk measures is explored. Finally, in Chapter 6, simulations on the topics presented in previous chapters are shown to shed a more practical light on the presentation of the previous chapters.
  • Blomgren, Roger Arne (2022)
    The cloud computing paradigm has risen, during the last 20 years, to the task of bringing powerful computational services to the masses. Centralizing the computer hardware to a few large data centers has brought large monetary savings, but at the cost of a greater geographical distance between the server and the client. As a new generation of thin clients have emerged, e.g. smartphones and IoT-devices, the larger latencies induced by these greater distances, can limit the applications that could benefit from using the vast resources available in cloud computing. Not long after the explosive growth of cloud computing, a new paradigm, edge computing has risen. Edge computing aims at bringing the resources generally found in cloud computing closer to the edge where many of the end-users, clients and data producers reside. In this thesis, I will present the edge computing concept as well as the technologies enabling it. Furthermore I will show a few edge computing concepts and architectures, including multi- access edge computing (MEC), Fog computing and intelligent containers (ICON). Finally, I will also present a new edge-orchestrator, the ICON Python Orchestrator (IPO), that enables intelligent containers to migrate closer to the users. The ICON Python orchestrator tests the feasibility of the ICON concept and provides per- formance measurements that can be compared to other contemporary edge computing im- plementations. In this thesis, I will present the IPO architecture design including challenges encountered during the implementation phase and solutions to specific problems. I will also show the testing and validation setup. By using the artificial testing and validation network, client migration speeds were measured using three different cases - redirection, cache hot ICON migration and cache cold ICON migration. While there is room for improvements, the migration speeds measured are on par with other edge computing implementations.
  • Laaja, Oskari (2022)
    Mobile applications have become common and end-users expect to be able to use either of the major platforms: iOS or Android. The expectation of finding the application in their respected platform stores is strongly present. The process of publishing mobile applications into these application stores can be cumbersome. The frequency of mobile application updates can be damaged by the heaviness of the process, reducing the end-user satisfaction. As manually completed processes are prone to human errors, the robustness of the process decreases and the quality of the application may diminish. This thesis presents an automated pipeline to complete the process of publishing cross-platform mobile application into App Store and Play Store. The goal of this pipeline is to make the process faster to complete, more robust and more accessible to people without technical knowhow. The work was done with design science methodology. As results, two artifacts are generated from this thesis: a model of a pipeline design to improve the process and implementation of said model to functionally prove the possibility of the design. The design is evaluated against requirements set by the company for which the implementation was done. As a result, the process used in the project at which the implementation was taken into use got faster, simpler and became possible for non-development personnel to use.
  • Keski-Hynnilä, Olli (2022)
    The COVID-19 pandemic moved the work force to work from home (WFH). This is also true for the internal startup Toska, who started the development of a new course feedback system (CFS) during the pandemic. This thesis compares existing literature about lean software development (LSD) and remote working to the results gained from the interviews of the people who worked on the CFS. This thesis explores previous work on topics of lean software development, remote working and work from home during COVID-19. Developers and other personnel of the CFS project were interviewed to gain insight into how COVID-19 and remote working in general affected the project. After taking a look into previous work, the study design of the thesis is discussed after which the results gained from the interviews are analyzed. Finally the interview results are compared to the previous work to see if the CFS project produced similar results. At the end of the thesis the limitations and future work of the project are discussed. The results gained from the interviews indicate similiarities and differences between other studies which are discussed in the background chapter. Similarities include things such as the developers missing the face-to-face interactions with each other and the ability to have ad-hoc discussions around a whiteboard when discussing. The project was considered a success by everyone working on it and based on the results lean software development and remote working are tools that should be taken into consideration when discussing how to do a software development project. Remote working in most cases improves the work-life balance of people and lean software development methods help empower the development team.