Browsing by Author "Laine, Sami"

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  • Improving the Security of Jupyter Autograding
    (2024-05-20) Laine, Sami
     Perustieteiden korkeakoulu | Master's thesis
    Jupyter Notebooks are a popular tool for science. They are commonly used in education to distribute and grade assignments. When teaching large courses, teachers often use automatic grading because it allows the course staff to focus on tutoring instead of grading. A commonly used tool for automatic grading of Notebooks is Nbgrader, which makes it possible to distribute, collect, and grade the assignments. However, the default grading process of Nbgrader executes the code on the grading teacher’s own user account, which introduces significant security risks. This thesis presents a method to run the grading in a secure, easy-to-use, and fast manner by using a Kubernetes cluster. In this thesis, a proof of concept is created for extending the grading functionality of Nbgrader, to run the grading in a container that is isolated from the teacher’s user account. The grading process is run in a container that is created and managed by Kubernetes, which provides a secure and scalable environment for running the grading process. This allows the grading process to be isolated from the teacher’s user account and the filesystem of the course platform, which significantly reduces the security risks of the grading process. This new grading process allows Nbgrader to be used in a more secure manner than it has been previously possible, and with further development, it can be integrated into a Jupyter environment running in a Kubernetes cluster.
  • Improving Trustworthiness of AI Solutions: A Qualitative Approach to Support Ethically-Grounded AI Design
    (2023) Vianello, Andrea; Laine, Sami; Tuomi, Elsa
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Despite recent efforts to make AI systems more transparent, a general lack of trust in such systems still discourages people and organizations from using or adopting them. In this article, we first present our approach for evaluating the trustworthiness of AI solutions from the perspectives of end-user explainability and normative ethics. Then, we illustrate its adoption through a case study involving an AI recommendation system used in a real business setting. The results show that our proposed approach allows for the identification of a wide range of practical issues related to AI systems and further supports the formulation of improvement opportunities and generalized design principles. By linking these identified opportunities to ethical considerations, the overall results show that our approach can support the design and development of trustworthy AI solutions and ethically-aligned business improvement.
  • Impulse control model of corporate cash management: Jump-diffusion approach.
    (2007) Laine, Sami
     School of Business | Master's thesis
  • Palomuurin konfigurointi IPv6-verkossa
    (2019-05-07) Laine, Sami
     Sähkötekniikan korkeakoulu | Bachelor's thesis