Blar i tittel Mastergradsoppgaver i teknologi - anvendt fysikk

Viser treff 16-35 av 67

    • Estimering av dempingskoeffisienter i elastiske materialer ved hjelp av bredbåndet ultralyd 

      Ali, Josoph Abuker (Master thesis; Mastergradsoppgave, 2009-07-01)
      Dette er en eksperimentell oppgave der et bredbåndet ultralydsystem er brukt til å undersøke hvordan dempingen av ultralydbølger i elastiske materialer, avhenger av frekvensen. For å gjøre denne undersøkelsen ble det utviklet en holder i pleksiglass med en ultralydtransduser på hver side. I denne holderen kan prøver av ulike materialer lett festes og undersøkes ved at holderen plasseres i et vannbad. ...

    • Estimering av egenskaper til naturlige klasser i radarbilder med en blandingsmodell 

      Moe, Åse Mari (Master thesis; Mastergradsoppgave, 2018-05-31)
      I løpet av de siste årene har isdekket i polhavet gått fra å være flerårsis til å bli en sesongbasert istype. Hvordan isen utvikler seg på sommeren vil avhenge av smeltevannandelen, blant annet på grunn av at smeltevannet har mindre albedo enn isen. For å estimere andelen smeltevann er det i denne oppgaven utviklet flere metoder som kan brukes på satellittbilder. Disse metodene bruker en statistisk ...

    • Experimental and numerical estimation of ultrasonic attenuation in polymers based on wave transmission methods 

      Grimstad, Trude (Master thesis; Mastergradsoppgave, 2013-07-01)
      PI-film, also known as Kapton, is a widely used polymer in the production of electronic equipment. Its use in printed circuit boards and sensors is increasing. It is therefore important to have knowledge about ultrasonic attenuation in the polymer. The main goal of this thesis was to investigate the attenuation of ultrasound through different polymers with different thicknesses. The presentation ...

    • Exploring the Behavior of Open-Source Diffusion Model Inpainting Algorithms 

      Halvorsen, Vebjørn (Master thesis; Mastergradsoppgave, 2023-01-26)
      The present study aimed to examine the performance of an open-source diffusion model inpainting algorithm under varying conditions of inpainting strength and mask radius. However, the results obtained were unexpected and raise significant concerns. Our findings indicate that the algorithm not only modifies the pixels within the designated mask, as intended, but also alters pixels out side of the ...

    • Extracting Information from Multimodal Remote Sensing Data for Sea Ice Characterization 

      Nilsen, Torjus (Mastergradsoppgave; Master thesis, 2021-06-01)
      Remote sensing is the discipline that studies acquisition, preparation and analysis of spectral, spatial and temporal properties of objects without direct touch or contact. It is a field of great importance to understanding the climate system and its changes, as well as for conducting operations in the Arctic. A current challenge however is that most sensory equipment can only capture one or fewer ...

    • Fluid-Thermal properties of electromagnetic heated water boli used in thermal treatment of superficial cancer 

      Martínez, Enrique de la Cruz (Master thesis; Mastergradsoppgave, 2007-06-15)
      Hyperthermia treatment (tissue heating up to 42-45 ºC) based on microwave applicators always uses a temperature controlled coupling medium consisting of deionized water. The bolus prevents blisters in the skin and acts as an impedance matching layer for the electromagnetic energy between the antenna and the treatment volume. Little is known whether practically realizable water flow-rates and other ...

    • Improved hardware stability and signal amplification in a medical microwave radiometer 

      Tobiassen, Alexander (Master thesis; Mastergradsoppgave, 2010-10-27)
      Breast cancer is one of the most frequent types of cancer in the female population today. Modern diagnostic modalities, while proven to be helpful within large scale screening programs, are inherently limited with regards to specificity and sensitivity, and use active methods for acquisition of information. A passive and non-invasive method for detection and diagnostic purposes could therefore be a ...

    • Imputation and classification of time series with missing data using machine learning 

      Dretvik, Vilde Fonn (Mastergradsoppgave; Master thesis, 2021-06-21)
      This work is about classifying time series with missing data with the help of imputation and selected machine learning algorithms and methods. The author has used imputation to replace missing values in two data sets, one containing surgical site infection (SSI) data of 11 types of blood samples of patients over 20 days, and another data set called uwave which contain 3D accelerometer data of several ...

    • Inference Guided Few-Shot Segmentation 

      Burman, Joel (Master thesis; Mastergradsoppgave, 2022-06-22)
      Few-shot segmentation has in recent years gotten a lot of attention. The reason is its ability to segment images from classes based on only a handful of labeled support images. This opens up many possibilities when the need for a big dataset is removed. To do this a few-shot segmentation network need to extract as much quality information from each support image as possible. In this thesis we ...

    • Information theoretic learning for pattern classification 

      Kvisle Storås, Ola (Master thesis; Mastergradsoppgave, 2007-12-17)
      This thesis is a study of pattern classification based on information theoretic criteria. Information theoretic criteria are important measures based on entropy and divergence between data distributions. First, the basic concepts of pattern classification with the well known Bayes classification rule as a starting point is discussed. We discuss how the Parzen window estimator may be used to ...

    • Information theoretic learning with K nearest neighbors : a new clustering algorithm 

      Vikjord, Vidar Vangen (Master thesis; Mastergradsoppgave, 2012-06-01)
      The machine learning field based on information theory has received a lot of attention in recent years. Through kernel estimation of the probability density functions, methods developed with information theoretic measures are able to use all the statistical information available in the data, not just a finite number of moments. However, by using kernel estimation, the methods are dependent on choosing ...

    • An initial assessment of the possibilities of fish catch prediction using Gaussian processes 

      Björk, Sara Maria (Master thesis; Mastergradsoppgave, 2016-12-15)
      The fishing and aquaculture industry is one of the largest industries of Norway. Enhanced knowledge of the distribution of fish in the ocean is important for an economical and sustainable fishing industry. This study investigates the possibilities of using Gaussian processes for regression within fish catch prediction. A dataset that combines catch reports from the Norwegian shipping company Havfisk ...

    • Introducing Soft Option-Critic for Blood Glucose Control in Type 1 Diabetes : Exploiting Abstraction of Actions for Automated Insulin Administration 

      Jenssen, Christian (Master thesis; Mastergradsoppgave, 2020-07-15)
      Type 1 Diabetes (T1D) is an autoimmune disease where the insulin-producing cells are damaged and unable to produce sufficient amounts of insulin, causing an inability to regulate the body's blood sugar levels. Administrating insulin is necessary for blood glucose regulation, requiring diligent and continuous care from the patient to avoid critical health risks. The dynamics governing insulin-glucose ...

    • Investigating robot navigation in health care with the Giraff telepresence robot 

      Kåven, Ove Henrik (Master thesis; Mastergradsoppgave, 2013-10-29)
      The Norwegian public healthcare system will not have the manpower to care for the elderly at the same level as now, unless technological solutions are found to make the most of the available manpower. This thesis investigates potential technologies for allowing the Giraff, a telepresence robot, to navigate and patrol an eldercare center autonomously, thus letting caregivers save time when checking ...

    • Investigating the effect of class-imbalance on convolutional neural networks for angiodysplasia detection 

      Kaspersen, Oskar Anstein (Master thesis; Mastergradsoppgave, 2019-10-31)
      In this thesis, we look at a deep learning approach to AD detection and focus specifically on the problem of class imbalance, which arises from the fact that lesions only occupy a small part of the images, by analyzing how weighting of the loss function can help address this issue. Balancing the weights of the foreground and background class in the cost-function was found to be crucial to achieve ...

    • Investigating the Impact of Susceptibility Artifacts on Adjacent Tumors in PET/MRI through Simulated Tomography Experiments 

      Olsen, Erlend Bredal (Mastergradsoppgave; Master thesis, 2021-06-01)
      For quantitative PET imaging, attenuation correction (AC) is mandatory. Currently, all main vendors of hybrid PET/MRI systems apply a segmentation-based approach to compute a Dixon AC-map based on fat and water images derived from in- and opposed-phase MR-images. Changes in magnetic susceptibility pose major problems for MRI, which may lead to artifacts resulting in tissue misclassification in the ...

    • An investigation of the robustness of distance measure-based supervised labelling of segmented remote sensing images 

      Kiærbech, Åshild (Master thesis; Mastergradsoppgave, 2019-06-03)
      Unsupervised clustering methods on remote sensing images have shown good results. However, this type of machine learning needs additional labelling to be an end-to-end classification in the same manner as traditional supervised classification. The automation of the labelling needs further exploration. We want to investigate the robustness of a supervised automatic labelling scheme by comparing a ...

    • Joint ranking and clustering based on Markov Chain transition probabilities learned from data 

      Løkse, Sigurd (Master thesis; Mastergradsoppgave, 2014-12-15)
      The focus of this thesis is to develop a Markov Chain based framework for joint ranking and clustering of a dataset without the need for critical user-defined hyper-parameters. Joint ranking and clustering may be useful in several respects, and may give additional insight for the data analyst, as opposed to the traditional separate ranking and clustering procedures. By coupling Markov ...

    • Laser Based Altimetry for Unmanned Aerial Vehicle Hovering Over a Snow Surface 

      Haugen, Hallvard (Master thesis; Mastergradsoppgave, 2017-06-02)
      A microwave radar for non-invasive snow stratigraphy measurements has been developed. Results were promising, but it failed to detect light powder snow in the air-snowpack interface. The aim of this thesis is to find and verify a system for estimating altitude on centimeter scale over a snow surface, independent of snow conditions. Also, relative pitch and roll angle estimation between the UAV and ...

    • Machine Learning for Classifying Marine Vegetation from Hyperspectral Drone Data in the Norwegian coast 

      Grue, Silje B.S. (Master thesis; Mastergradsoppgave, 2022-05-30)
      Along the Norwegian coasts the presence of blue forests are the key marine habitats. Due to increased anthropogenic activity and climate change, the health and extent of the blue forests is threatened. However, no low-cost, reliable system for monitoring blue forests exists in Norway at this time. This thesis studied machine learning methods to classify marine vegetation from hyperspectral data ...