Sökning: "driving rain"
Visar resultat 1 - 5 av 20 uppsatser innehållade orden driving rain.
1. Surface Runoff on Green Urban Areas : A study on driving forces behind surface runoff generaiton
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Luft-, vatten- och landskapsläraSammanfattning : Recent flooding events, such as the one in Germany 2021 have caused irreversible damages to infrastructure and lives. The aftermath of events like these have underlined the importance of an accurate risk management by predicting them in urban areas. LÄS MER
2. Lek, lärande & rörelse på bostadsgården med dagvatten som resurs
Master-uppsats, SLU/Dept. of Landscape Architecture, Planning and Management (from 130101)Sammanfattning : Föreliggande studie utreder hur dagvatten kan användas som resurs för att främja lek, lärande och rörelse på bostadsgården. I urbana sammanhang ses ofta dagvatten som ett problem då stora vattenflöden överbelastar vår infrastruktur med förödande konsekvenser. LÄS MER
3. Real-time Unsupervised Domain Adaptation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Machine learning systems have been demonstrated to be highly effective in various fields, such as in vision tasks for autonomous driving. However, the deployment of these systems poses a significant challenge in terms of ensuring their reliability and safety in diverse and dynamic environments. LÄS MER
4. Characterization of Landscape Structures and Precipitation in relation to Flooding events in Pampa Deprimida : A Minor Field Study in Argentina
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Luft-, vatten- och landskapsläraSammanfattning : The purpose of the thesis is to characterize flood events within the agricultural fields of flooding Pampa in Argentina. The characterization divides the flat landscape into flood prone areas and endeavour at linking driving factors to flood response based on past events. LÄS MER
5. Online Unsupervised Domain Adaptation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Deep Learning models have seen great application in demanding tasks such as machine translation and autonomous driving. However, building such models has proved challenging, both from a computational perspective and due to the requirement of a plethora of annotated data. LÄS MER