Sökning: "Correction factor"

Visar resultat 1 - 5 av 79 uppsatser innehållade orden Correction factor.

  1. 1. Development of Spectroscopic Measurements for Raman and Thomson Scattering Diagnostics ——Applications in Combustion and Plasma

    Master-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Förbränningsfysik

    Författare :Miaoxin Gong; [2019]
    Nyckelord :Raman scattering; Raman spectroscopy; Thomson scattering; stray light suppression; periodic shadowing; high dynamic range imaging; digital micro-mirror device; DMD; laminar flames; combustion; gas discharge; plasma; laser diagnostics; spectrometer; improved spectroscopy; spectroscopy; Physics and Astronomy;

    Sammanfattning : This thesis work concerns methods for improved spectroscopy including stray-light suppression, dynamic range improvement and signal enhancement. These methods were applied in Raman and Thomson- scattering spectroscopy in combustion and plasma. LÄS MER

  2. 2. The Nordic Prediction Method For Railway Traffic Noise : Improvements of the current corrections forrailway bridges, switches and crossings

    Master-uppsats, KTH/Byggnadsmaterial; KTH/Byggnadsmaterial

    Författare :KRISTÍN HELGADÓTTIR; RAGNHEIÐUR BJÖRNSDÓTTIR; [2019]
    Nyckelord :The Nordic Prediction Method; Railway traffic; Railway noise; Noise measurements; Acoustics; Steel bridges; Concrete bridges; Switches; Railway crossings; Correction factor; Correction for track condition;

    Sammanfattning : Railway noise is a very important and growing health hazard in today´s society.Railway systems pass through towns and cities and create noise. When trainsride through or over railway bridges, switches and crossings the noise increasessubstantially, causing great annoyance to the residents in the area. LÄS MER

  3. 3. Heating systems in small houses : A comparison between geothermal heating and district heating

    M1-uppsats, KTH/Byggteknik och design; KTH/Byggteknik och design

    Författare :Victor Fredriksson; Bane Gluhajic; [2019]
    Nyckelord :Heating system; Geothermal heating; District heating; Comparison; Energy performance; Värmesystem; Bergvärme; Fjärrvärme; Jämförelse; Energiprestanda;

    Sammanfattning : District heating and geothermal heating are in present times two established heating systems that are often compared against each other. The purpose of this work is to describe which factors influence the choice of heating system during the planning stage and what the costs are for each system. LÄS MER

  4. 4. Predicting the area of industry : Using machine learning to classify SNI codes based on business descriptions, a degree project at SCB

    Kandidat-uppsats, Umeå universitet/Statistik; Umeå universitet/Statistik

    Författare :Philip Dahlqvist-Sjöberg; Robin Strandlund; [2019]
    Nyckelord :machine learning; classification; gradient boosting; data analysis; NLP; SNI; SCB;

    Sammanfattning : This study is a part of an experimental project at Statistics Sweden,which aims to, with the use of natural language processing and machine learning, predict Swedish businesses’ area of industry codes, based on their business descriptions. The response to predict consists of the most frequent 30 out of 88 main groups of Swedish standard industrial classification (SNI) codes that each represent a unique area of industry. LÄS MER

  5. 5. Analysing Raman spectra of crystalline cellulose degradation by fungi using artificial neural networks

    Kandidat-uppsats, Lunds universitet/Beräkningsbiologi och biologisk fysik; Lunds universitet/Institutionen för astronomi och teoretisk fysik

    Författare :Sebastian Hutteri; [2019]
    Nyckelord :Raman spectroscopy; artificial neural networks; saprotrophic fungi; cellulose; Physics and Astronomy;

    Sammanfattning : This thesis investigates the use of artificial neural networks for classifying Raman spectra of partially degraded cellulose samples by fungal species. A multilayer perceptron configuration of 4 hidden layers and 128 hidden nodes was able to classify a set of 60 samples with an overall prediction accuracy of 0.55. LÄS MER