Search for dissertations about: "fire machine"

Found 5 swedish dissertations containing the words fire machine.

  2. 1. Multispectral Remote Sensing and Deep Learning for Wildfire Detection

    Author : Xikun Hu; Yifang Ban; Ioannis Gitas; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; active fire detection; biome; multi-criteria; Sentinel-2; Landsat-8; burned area mapping; deep learning; semantic segmentation; machine learning.; aktiv branddetektering; biom; multikriterietillvägagångssätt; Sentinel-2; Landsat-8; kartläggning av bränt område; djupinlärning; semantisk segmentering; maskininlärningsmetoderna; Geoinformatik; Geoinformatics;

    Abstract : Remote sensing data has great potential for wildfire detection and monitoring with enhanced spatial resolution and temporal coverage. Earth Observation satellites have been employed to systematically monitor fire activity over large regions in two ways: (i) to detect the location of actively burning spots (during the fire event), and (ii) to map the spatial extent of the burned scars (during or after the event). READ MORE

  4. 2. Low Frequency Impact Sound in Timber Buildings : Simulations and Measurements

    Author : Jörgen Olsson; Andreas Linderholt; Leif Kari; Linnéuniversitetet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Low-frequency; impact sound; light weight floor; timber joist floor; tapping machine; multi-storey timber building; frequency response functions.; Stegljud; Byggteknik; Civil engineering;

    Abstract : An increased share of construction with timber is one possible way of achieving more sustainable and energy-efficient life cycles of buildings. The main reason is that wood is a renewable material and buildings require a large amount of resources. READ MORE

  5. 3. Deep Learning for Geo-referenced Data : Case Study: Earth Observation

    Author : Nosheen Abid; Marcus Liwicki; Muhammad Zeshan Afzal; Luleå tekniska universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Artificial Intelligence; Machine Learning; Earth Observation; Computer Vision; Machine Learning; Maskininlärning;

    Abstract : The thesis focuses on machine learning methods for Earth Observation (EO) data, more specifically, remote sensing data acquired by satellites and drones. EO plays a vital role in monitoring the Earth’s surface and modelling climate change to take necessary precautionary measures. READ MORE

  6. 4. Large-Scale Multi-Source Satellite Data for Wildfire Detection and Assessment Using Deep Learning

    Author : Xikun Hu; Yifang Ban; Martin Wooster; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Wildfire; Remote Sensing; Active Fire Detection; Burned Area Mapping; Burn Severity Assessment; Sentinel-2; Landsat; Sentinel-1; Deep Learning; Semantic Segmentation; Image Translation; Skogsbrand; fjärranalys; aktiv branddetektering; kartläggning av bränt område; bedömning av brännskador; Sentinel-2; Landsat; Sentinel-1; djupinlärning; semantisk segmentering; bildöversättning.; Geoinformatik; Geoinformatics;

    Abstract : Earth Observation (EO) satellites have great potential in wildfire detection and assessment at fine spatial, temporal, and spectral resolutions. For a long time, satellite data have been employed to systematically monitor wildfire dynamics and assess wildfire impacts, including (i) to detect the location of actively burning spots, (ii) to map the spatial extent of the burn scars, (iii) to assess the wildfire damage levels. READ MORE

  7. 5. Stimulated autogenous self-healing of mechanically and thermally cracked cementitious materials

    Author : Magdalena Rajczakowska; Andrzej Cwirzen; Karin Habermehl-Cwirzen; Hans Hedlund; Erik Schlangen; Luleå tekniska universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Byggmaterial; Building Materials;

    Abstract : It is estimated that each year, approximately 8 billion cubic meters of concrete are produced worldwide, a vast number comparable to 1 m3 per person, making the construction industry a major contributor to overall global CO2 emissions. Throughout the manufacturing process of the most common cement binder, ordinary Portland cement (OPC), CO2 emissions reach 842 kg per ton of clinker produced. READ MORE