Your search resulted in 4 documents.
Practice Makes Perfect: A Biodeterioration Diagnostics Database that Makes Practice
2008 - IRG/WP 08-10648
Replacement of bio-based materials deteriorated by pests costs billions annually and wastes natural resources. Wood replacement rates have remained relatively stable despite significant advances in wood preservation. This may be explained, in part, by poor end-use by uninformed users and by inadequate pest management once products are in service. This problem may be exacerbated by two opposing fac...
J S Schilling
The amazing wooden churches from Northern Romania - learning from the past, restoring for the future, preserving the present valuable heritage of forgotten wood building tradition
2009 - IRG/WP 09-10683
The beauty and the uniqueness of the north-western region of Romania called “Maramureş” are well known in Europe. Surrounded by mountains, the region remained to some extend isolated from modern influences, preserving the local village architecture and craftsman traditions learnt and passed on from generation to generation. Local folklore and past heritage sets you back centuries ago when...
R Craciun, R Möller
The InnovaWood Module Bank: Building an international e-learning platform for shared MSc courses in wood science and technology
2019 - IRG/WP 19-50355
The InnovaWood Module Bank is a shared e-Learning platform for standalone science, technology and education modules in wood science. A group of members of InnovaWood have committed to jointly develop this platform. The institutes benefit in that they can widen the range of courses they offer and use their teaching capacities more efficiently. Students obtain the possibility to take online courses ...
M Irle, U Kies, H Militz, P Sauerbier, M Vieux, A Prosic, B Wolfsberger, F Pichelin, I Mayer
Lab-scale termite damage synthesis using least squares generative adversarial networks
2020 - IRG/WP 20-20674
This manuscript investigated the feasibility of least squares generative adversarial networks (LSGAN) to generate synthetic images of lab-scale termite damage based on AWPA E1 standard, to push machine-learning forward into wood science field and to ameliorate the lack of a termite damage dataset. We leveraged LSGAN to learn the distribution of 203 uniquely termite damaged samples from previous ex...
D J V Lopes