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The time consumption and productivity of TMK-300-accumulating felling head in whole tree felling
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Lapset, tunteet ja tunnetaitokirjallisuus – havainnointitutkimus alakoululaisista tunnetaitokirjallisuuden vastaanottajina
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Developing Organizational Change through Transformational Leadership. Assessment of a Global People Management Model at an IT Company
No full textLainsoveltajan opas asiantuntijoille — Asiakirjahallintaan liittyvät lait, lainsäädäntöön liittyvät näkemykset ja lakien soveltamisessa koetut haasteet asiakirja-ammattilaisen työssä
No full textSeikkaileva miessankari. Traditiot ja keskusta–marginalian murtumat kahdessa eurooppalaisessa sarjakuvassa
No full text"Slår man sig samman blir musklerna större" - Diskurser kring samlokaliserade skolor i offentliga medier
No full textSTOPA: A Dataset of Systematic VariaTion Of DeePfake Audio for Open-Set Source Tracing and Attribution
No full textSTOPA is a dataset for source tracing and attribution of deepfake audio, identifying which synthesis system generated a given utterance. It includes over 700,000 synthetic speech samples, generated using 13 distinct systems with controlled variation across 8 acoustic models and 6 vocoders. The dataset follows ASVspoof2019 Logical Access protocols and uses speakers from the VCTK corpus. It supports open-world evaluation, where test utterances are compared against individual source hypotheses without assuming closed-set conditions. Rich metadata and pairwise trial protocols enable fine-grained attribution at the level of attack, acoustic model, or vocoder. All audio is provided as 16-bit PCM WAV at 16 kHz. Metadata includes transcription, silence regions, WER, and system labels. License: CC BY 4.0Audio type: Synthetic onlyLanguage: English (VCTK-based