Search results for "Mould"
showing 4 items of 44 documents
Machine learning analysis of e-nose signal in early detection of mold contamination in buildings
2017
Grzyb rozwijający się na ścianach budynków jest głównym powodem zjawiska, które nazwano Syndromem Chorego Budynku. Wolne związki organiczne emitowane przez grzyby mogą być wykryte różnymi metodami, m.in. na podstawie chromatografii, ale także za pomocą matryc czujników gazowych. Wszystkie tego typu narzędzia generują sygnały elektryczne, które można analizować za pomocą odpowiednich technik statystycznych. Praca skupia się na zastosowaniu nadzorowanych i nienadzorowanych technik uczenia maszynowego w ocenie sygnału pochodzącego z elektronicznego nosa.
Evaluation of natural products to control some rose diseases.
2008
Standardisation of methods for assessing mould germination: a workshop report.
2006
International audience; The first workshop on predictive mycology was held in Marseille, France, 2–4 February 2005 under the auspices of the French Microbiological Society. The purpose of the workshop was to list the different techniques and definitions used by scientists for assessing mould germination and to evaluate the influence of the different techniques on the experimental results. Recommendations were made when a large consensus was obtained. In order to facilitate the study of germination, alternative methods to microscopic examination were examined.
Dampness and student-reported social climate: two multilevel mediation models.
2021
Background Little previous research has analysed the relationship between schools' indoor air problems and schools' social climate. In this study, we analysed a) whether observed mould and dampness in a school building relates to students' perceptions of school climate (i.e. teacher-student relationships and class spirit) and b) whether reported subjective indoor air quality (IAQ) at the school level mediates this relationship. Methods The data analysed was created by merging two nationwide data sets: survey data from students, including information on subjective IAQ (N = 25,101 students), and data from schools, including information on mould and dampness in school buildings (N = 222). The …