Selaus koulutusohjelman mukaan kokoelmassa Diplomityöt ja Pro gradu -tutkielmatSchool of Engineering Science, Laskennallinen tekniikka
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3D reconstruction of logs from board images
(2022)Sawmills nowadays are heavily automated and especially sawing process optimisation could improve overall yield of sawn timber. The main focus of this thesis work is to create a method to reconstruct a 3D-model of a log ... -
A comparative analysis of object tracking methods
(2023)Multiple object tracking consists of tracking several targets simultaneously. This thesis focuses on demonstrating the effectiveness of random finite set-based methods in object tracking, considering both single-object ... -
A comparative study between rotational and virtual inertia : role of liquid air energy storage as a source of inertia in future power systems
(2022)Using power system frequency response simulations, this study develops understanding of the different factors that influence the capacity of fast energy storage systems and inverter capacity that can compensate for the ... -
A risk model with renewal shot-noise Cox process
(2019)Catastrophic events may lead to sudden changes in the claim arrival rate and as a result it is difficult to predict the likelihood for the occurrence of these events. These random fluctuation cannot be modeled as a homogeneous ... -
Accelerated annotation of 3D medical images using interactive segmentation
(2023)This thesis explores the use of interactive segmentation on 3D medical CT scan images. Interactive segmentation allows users to manually guide image division, enhancing the precision of medical imaging analysis. In this ... -
Active learning for plankton recognition
(2022)Plankton is essential part of the ocean ecosystem as it is an important food source for many marine life, both large and small and is also oxygen producer. Therefore, its quantity and condition must be monitored and its ... -
Additive manufacturing of medications and static light scattering analysis of mesoporous structures
(2019)The main focus of the project was on the development of a method for three-dimensional printing of matrixes of drug carriers. For implementation, a wide instruction was applied, because for the solution of problems it was ... -
AFM investigation of the influence of relative humidity on the electrical potential of tin oxide films
(2021)The influence of the relative humidity (RH) of the air on the electric potential of the materials' surfaces was investigated. Nickel-doped tin dioxide films were synthesized by magnetron sputtering in argon plasma. Atomic ... -
Analysis of factors affecting the development of liquidity and its forecast with hierarchical clustering on principal components
(2021)In order to get a glimpse of the current state of the companies on a broader level, the development of liquidity and the difference between the cash flow forecast and its realized values were examined to find possible ... -
Analysis of survey data by numerical modelling
(2020)Analysing survey data poses a challenge of often being based on human feelings, which cannot be measured by objective numerical values. The Finnish Institute of Occupational Health has formulated a survey to measure the ... -
Assessment of statistical relationship between cloud indices and relative photovoltaic (PV) production data
(2019)The primary need and necessity for survival is energy. Currently, mankind's reliance primarily on fossils fuels which are non-renewable and rapidly depleting. Furthermore, the emission of greenhouse gases from these finite ... -
Backward stochastic differential equations with applications
(2018)In this thesis we study backward stochastic differential equations driven by a Brownian motion and by a Levy process and their applications, focusing on their applications to financial markets. We give results on the ... -
Bayesian optimal design in X-ray tomography
(2020)This thesis focuses on Bayesian optimal design and its applications to X-ray tomography. X-ray tomography is a well-known setting where X-rays are projected at an object. X-ray intensity data is recorded on the other side ... -
Bayesian parameter estimation with applications to extreme ocean waves
(2020)Sea state observations decomposed into a wave spectrum model is one direct way of monitoring ocean dynamics with the aid of statistical methods. The frequentist and Bayesian methods play prominent roles in estimating the ... -
Breast cancer diagnostic using machine learning : applying supervised learning techniques to Coimbra and Wisconsin datasets
(2023)Breast cancer poses a significant global health concern, with approximately 2.2 million new cases and 700,000 deaths reported in 2020. Traditional diagnostic approaches which predominantly depend on expert judgement, have ... -
Characterisation of low gain avalanche detectors for the CMS experiment
(2020)The aim of this thesis was to measure the current-voltage and capacitance-voltage characteristics of the latest batch of Ultra-Fast Silicon Detectors produced by Fondazione Bruno Kessler and evaluate the parameters of the ... -
Characterization and testing of novel single core phosphate fibers
(2019)This work is devoted to the study of novel optical fibers doped with Er3+ ions. Fibers were drawn from the phosphate glasses with different compositions. One of the optical fibers was drawn from a heat-treated preform in ... -
Characterization of irradiated and non-irradiated Low Gain Avalanche Detectors (LGADs)
(2021)The objective of this work was to characterize the radiation hardness of the Fondazione Bruno Kessler (FBK) Ultra-Fast Silicon Detectors (UFSD) UFSD3.2 batch by comparing their capacitance-voltage characteristics before ... -
Classifying customer companies in an enterprise resource planning system using machine learning methods
(2022)Information systems such as smart phone applications collect large amounts of data about their users. The data is used mostly for the system’s primary task, but machine learning methods can be used to get additional value ... -
Clustering and prediction with a Gaussian process mixture model
(2021)Gaussian processes provide a powerful Bayesian approach to many machine learning tasks. Unfortunately, their application has been limited by the cubic computational complexity of inference. Mixtures of Gaussian processes ...