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Osuva on Vaasan yliopiston avoin julkaisuarkisto. Osuva sisältää Vaasan yliopiston omat julkaisut, opinnäytteet ja tieteellisten artikkeleiden rinnakkaistallenteet. Osuvaan sisältyy julkaisujen viitetietoja, tiivistelmiä ja kokotekstejä. Sähköisten arkistokokoelmien sisältö ei ole luettavissa verkossa.

Kokoelmat Osuvassa

Viimeksi tallennetut

  • Parametric life-cycle assessment for configurable products in high-mix manufacturing
    Shamsuzzoha, Ahm; Mayanti, Bening; Helo, Petri (Elsevier, 2026)
    Artikkeli
    High-mix manufacturers face challenges in delivering product-specific environmental data at required time. Traditional life cycle assessment (LCA) is a post-hoc tool that requires intensive manual work in calculating product-variant impact. This study proposes a solution by developing and evaluating a parametric LCA that can generate product-specific environmental assessments when production orders are completed. Using a design science approach, the proposed solution is tested in pipe manufacturing which produces many product variants. The study methodologically contributes to modelling multi-process parametric LCA for various products using the product geometry and routing running time as main parameters. Moreover, the study also positions parametric LCA as a core methodology for product service system transition in which automated environmental data is considered as a service when bundled with physical products in high-mix manufacturing supply chains. The paper focuses on addressing the challenges of managing a wide variety of products and generating self-declared life-cycle analysis reports for each product variant. This solution is designed to develop the product configuration process using up-to-date software solutions that support order-handling processes in case-by-case situations for companies, while maintaining environmental sustainability.
  • Talousopetuksen kehittämisestä: vastaus Kortesalmelle, Puustiselle ja Poikolaiselle
    Kalmi, Panu (Taloustieteellinen yhdistys, 2025)
    Artikkeli
    Kiitän Marilla Kortesalmea, Mikko Puustista ja Janne Poikolaista monipuolisesta ja hyvin perustellusta vastineesta pääkirjoitukseeni Kansantaloudellisen aikakauskirjan numerossa 1/2025. Olen heidän kanssaan monesta asiasta hyvin samaa mieltä. Käytän tilaisuutta hyväkseni korjatakseni yhden keskeisen väärinymmärryksen, ja samalla yritän kirkastaa omaa viestiäni.
  • Mitä annettavaa taloustieteellä voisi olla talousosaamisen kouluopetukselle?
    Kalmi, Panu (Taloustieteellinen yhdistys, 2025)
    Artikkeli
  • HandoffFL: Efficient Communication in Federated Learning Via Asynchronous Layer-Wise Handoff Training
    Zhang, Wenjun; Liu, Xiaoli; Tarkoma, Sasu (IEEE, 2026)
    Artikkeli
    Federated Learning (FL) enables collaborative training without sharing raw data, yet conventional synchronous approaches suffer from poor scalability and high communication costs, imposing heavy burdens on resource-constrained clients in heterogeneous edge environments. While asynchronous FL reduces heterogeneous stragglers, it introduces severe staleness and convergence degradation. Recent layer-wise FL methods reduce resource consumption by decomposing training into sequential layer-level tasks; however, they still rely on rigid round-based synchronization and therefore lack adaptability to dynamic client availability and network fluctuations. We propose HandoffFL, an event-driven asynchronous layer-wise FL framework built on a real-time message-passing monitoring architecture. HandoffFL organizes training into layer-level stages, where clients train one layer at a time with frozen prefixes. Transitions between layers are triggered by adaptive convergence events, enabling clients to progressively hand off converged layers and advance at their own pace. To support convergence detection at intermediate layers, the framework introduces temporal classifiers and further applies layer-specific staleness-aware aggregation with exponential decay and truncation. Extensive experiments on MNIST, Fashion-MNIST, and CIFAR-10 with multiple model architectures demonstrate that HandoffFL substantially reduces wall-clock training time and communication overhead compared to synchronous layer-wise FL, while maintaining comparable accuracy and robustness under heterogeneous client conditions compared with asynchronous FL.
  • BridgeLoRA: Privacy-Preserving Collaborative Skip-Layer Connectors for Efficient Transformer Fine-Tuning at the Edge
    Toivonen, Vilhelm; Su, Xiang; Liu, Xiaoli; Tarkoma, Sasu; Hui, Pan (IEEE, 2026)
    Artikkeli