Bygg- og anleggsbransjen utgjør en svært risikabel arbeidsplass, noe som gjenspeiler seg i omfanget av arbeidsulykker. Av berørte parter er utenlandske, og spesielt polske arbeidere, overrepresentert på skadestatistikken i forbindelse med de mest alvorlige arbeidsulykkene (Mostue et al., 2022). For å sikre en trygg arbeidsplass for alle aktører anses det som nødvendig å drive kontinuerlig ...

Denne studien undersøker hvilke utfordringer organisasjoner i tunnelbransjen møter i utviklingen av en positiv sikkerhetskultur. En sektor som har en av de høyeste ulykkesratene i landet (Arbeidstilsynet, 2019). Sikkerhetskultur er identifisert som en viktig faktor i arbeidet mot en tryggere arbeidsplass. Tidligere forskning viser imidlertid at det fortsatt er behov for å utforske måter å optimalisere ...

This paper serves as the first empirical study on self-supervised pre-training on partially supervised learning, an emerging yet unexplored learning paradigm with missing annotations. This is particularly important in the medical imaging domain, where label scarcity is the main challenge of practical applications. To promote the awareness of partially supervised learning, we leverage partially ...

We introduce a novel methodological advancement by clustering paired near-surface air temperature with the planetary boundary layer height to characterize intra-city clusters for analytics. To illustrate this approach, we analyze three heatwaves (HWs): the 2019 HW in Paris, the 2018 HW in Montreal, and the 2017 HW in Zurich. We assess cluster-based characteristics before, during, and after ...

Both the Soret and Q bands of chlorin e6 complexes blueshift on going from Zn to Pd to Pt as the coordinated metal, establishing the latter two complexes as hypsochlorins. DFT/TDDFT calculations indicate that the blueshifts appear to be related to the presence of the electronegative metal ion, which lowers the orbital energies of the HOMO and HOMO-1, while leaving the LUMOs relatively unaffected.

Millions of ionograms are acquired annually to monitor the ionosphere. The accumulated data contain untapped information from a range of locations, multiple solar cycles, and various geomagnetic conditions. In this study, we propose the application of deep convolutional neural networks to automatically classify and scale high-latitude ionograms. A supervised approach is implemented and the networks ...

Programmable nanoscale carriers, such as liposomes and DNA, are readily being explored for personalized medicine or disease prediction and diagnostics. The characterization of these nanocarriers is limited and challenging due to their complex chemical composition. Here, we demonstrate the utilization of surface-enhanced Raman spectroscopy (SERS), which provides a unique molecular fingerprint of ...

EISCAT_3D is a project to build a multi-site phased-array incoherent scatter radar system in northern Fenno-Scandinavia. We demonstrate via numerical simulation how useful monochromatic images taken by a multi-point imager network are for auroral research in the EISCAT_3D project. We apply the generalized aurora computed tomography (G-ACT) method to modelled observational data from real instruments, ...

Microfossil classification is an important discipline in subsurface exploration, for both oil & gas and Carbon Capture and Storage (CCS). The abundance and distribution of species found in sedimentary rocks provide valuable information about the age and depositional environment. However, the analysis is difficult and time-consuming, as it is based on manual work by human experts. Attempts to automate ...