Blar i Brage NMBU på forfatter "Liland, Kristian Hovde"
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Model-based pre-processing in Raman spectroscopy of biological samples
Liland, Kristian Hovde; Kohler, Achim; Afseth, Nils Kristian (Journal article; Peer reviewed, 2016)Model-based pre-processing has become wide spread in spectroscopy and is the standard procedure in Fourier-transform infrared spectroscopy. It has also been shown to give valuable contributions in Raman spectroscopy. ... -
Much faster cross‐validation in PLSR‐modelling by avoiding redundant calculations
Liland, Kristian Hovde; Stefansson, Petter; Indahl, Ulf Geir (Peer reviewed; Journal article, 2020) -
Multi block analysis of gastrointestinal neuroendocrine tumors data using response oriented sequential alternation (ROSA)
Azadi, Ghazal Gazelle (Master thesis, 2021)Gastrointestinal neuroendocrine tumors (NETs) are slow-growing tumors. In this type of cancer, survival rate is an important factor. The current study considers the number of survival days as the target variable and tries ... -
Multiblock-model analysis of multi-source Alzheimer’s disease data
Randhawa, Jora Singh (Master thesis, 2020)Alzheimer’s Disease (AD) is the most common cause of dementia in the world. It is a disorder that causes brain cells to degenerate and eventually dies, which causes a continuous decline in memory, cognitive abilities and ... -
Multitemporal Feature-Level Fusion on Hyperspectral and LiDAR Data in the Urban Environment
Kuras, Agnieszka Kinga; Brell, Maximilian; Liland, Kristian Hovde; Burud, Ingunn (Peer reviewed; Journal article, 2023) -
Natural Language Processing and Topic Modeling for Exploring the Vegetarian and Vegan Trends
Olavsrud, Marius Aleksander (Master thesis, 2020)The purpose of this thesis is to examine how topic modeling can be used as a tool to explore large sets of text data. This thesis is written on assignment from Nofima Food Research Institute. A set of about 52 000 unknown ... -
Near infrared hyperspectral imaging in transmission mode: assessing the weathering of thin wood samples
Smeland, Knut Arne; Liland, Kristian Hovde; Sandak, Jakub; Sandak, Anna; Gobakken, Lone Ross; Thiis, Thomas Kringlebotn; Burud, Ingunn (Journal article; Peer reviewed, 2016) -
New methodologies in sensory and consumer research with preadolescents to guide product development of healthy, child-centred food
Galler, Martina (PhD Thesis;2021:89, Doctoral thesis, 2021)Childhood obesity is one of the most serious public health challenges of the twenty-first century (WHO, 2018). In this context, finding ways to make the healthier food choices the preferred ones, can be a valuable contribution ... -
Non-linear shrinking of linear model errors
Helin, Runar; Indahl, Ulf Geir; Tomic, Oliver; Liland, Kristian Hovde (Journal article; Peer reviewed, 2023) -
Optimizing transcriptome analysis using short-read RNA-seq in Atlantic salmon
Kirste, Katrine Hånes (Master thesis, 2016-09-14)Målet med studiet var å sammenligne genome-guided assembly og de novo assembly av transcriptomdata, for å finne ut hvilken metode som burde anbefales. De novo assembly er mye mere krevende angående datalagringsplass og ... -
Orders of magnitude speed increase in Partial Least Squares feature selection with new simple indexing technique for very tall data sets
Stefansson, Petter; Indahl, Ulf Geir; Liland, Kristian Hovde; Burud, Ingunn (Peer reviewed; Journal article, 2019)Feature selection is a challenging combinatorial optimization problem that tends to require a large number of candidate feature subsets to be evaluated before a satisfying solution is obtained. Because of the computational ... -
Predicting grain yield by utilizing multispectral images and convolutional neural network
Idris, Sara Elisabeth (Master thesis, 2023)According to the UN’s sustainability goals, hunger should have been eradicated by 2030, but the number is going the wrong way, with around 800 million people who suffer from undernourishment in 2022. Therefore, there is a ... -
Predicting treatment outcome of colorectal cancer from MRI images using machine learning
Søvdsnes, Marthe Susann (Master thesis, 2021)In this thesis different machine learning algorithms have been utilised to predict treatment outcome for patients with colorectal cancer. The predicted treatment endpoint was overall survival. The patient cohort included ... -
Prediction of passenger load on busses in Oslo using data from Automatic Data Collection-systems
Jarmund, Johanne Krokene (Master thesis, 2021)Public transport is key to reducing the usage of private vehicles, and by extension carbon emission in urban areas. Ruter is responsible planning and coordinating public transport in Oslo. Through different Automatic Data ... -
Predictive maintenance for fouling in a plate heat exchanger
Mohammad, Numan (Master thesis, 2019)Heat exchangers are very common in industrial processes, such as waste heat recovery and the food and chemical industry as well as in daily life like air-conditioning. One of the major hurdles in the performance, process, ... -
Preprocessing of industrial time series for soft sensor development
Sedal, Astrid Hæve (Master thesis, 2023)With increasing population growth, the demand for food and proteins rises. The need for protein from poultry is projected to increase by 17.8% by 2030, and poultry production in Norway has never been higher. Nortura at ... -
Preprocessing of spectral data in the extended multiplicative signal correction framework using multiple reference spectra
Skogholt, Joakim; Liland, Kristian Hovde; Indahl, Ulf Geir (Journal article; Peer reviewed, 2018) -
Prokaryote classification : method development and novel insight in 16S ribosomal RNA-based classification
Vinje, Hilde (PhD Thesis;2016:95, Doctoral thesis, 2016)The main objective of this thesis is the improvement of prokaryotic classification based on the 16S ribosomal RNA. As a result of the shift in sequencing technology, generating enormous amounts of sequencing data and the ... -
Reduction and inhibition of Listeria monocytogenes in cold-smoked salmon by Verdad N6, a buffered vinegar fermentate, and UV-C treatments
Heir, Even; Liland, Kristian Hovde; Carlehög, Mats; Holck, Askild Lorentz (Journal article; Peer reviewed, 2018) -
Reinforcement learning for grid control in an electric distribution system
Solberg, Vegard Ulriksen (Master thesis, 2019)The increasing amount of variable renewable energy (VRE) sources such as solar and wind power in the power mix brings new challenges to existing power system infrastructure. A fundamental property of an electric power ...