2023

This doctoral thesis concerns the optimization of multi-stage manufacturing processes. In multi-stage manufacturing, the overall manufacturing process comprises several subprocesses, i.e. stages. Because real-world manufacturing processes are costly in terms of materials, labor hours, energy, and CO2 emissions, physics-based simulations can be used to represent individual manufacturing stages. One drawback of physics-based simulations is their…

This thesis considers parametric scenario based methods for Space-Time Adaptive Processing (STAP) in airborne bistatic radar systems. STAP is a multidimensional filtering technique used to mitigate the influence of interference and noise in a target detector. To be able to perform the mitigation, an accurate estimate is required of the associated space-time covariance matrix to…

This dissertation explores advancements in future navigation satellite systems, proposing and analyzing solutions at system, signals, and user level. The objective of this work has been to seek for performance improvements, acting at various levels of the Global Navigation Satellite System (GNSS) value chain, yet fulfilling possible upcoming needs and constraints. In this context, this…

In many modern signal processing applications, traditional machine learning and pattern recognition methods heavily rely on the having a sufficiently large amount of data samples to correctly estimate the underlying structures within complex signals. The main idea is to understand the inherent structural information and relationships embedded within the raw data, thereby enabling a wide…

This thesis focuses on wearables for health status monitoring, covering applications aimed at emergency solutions to the COVID-19 pandemic and aging society. The methods of ambient assisted living (AAL) are presented for the neurodegenerative disease Parkinson?s disease (PD facilitating ?aging in place? thanks to machine learning and around wearables – solutions of mHealth. Furthermore, the…

Introduction The balanced scorecard (BSC) is a comprehensive performance evaluation (PE) tool. Stakeholders such as patients and healthcare workers (HCWs) are rarely engaged in BSC implementation at health care organizations (HCOs). The four core studies of this dissertation aim to 1. assess the impact of BSC implementation on HCWs? satisfaction, patient satisfaction, and financial performance,…

Due to a variety of potential barriers to sample acquisition, many of the datasets encountered in important classification applications, ranging from tumor identification to facial recognition, are characterized by small samples of high-dimensional data. In such situations, linear classifiers are popular as they have less risk of overfitting while being faster and more interpretable than…

In the realm of traffic monitoring, efficient video analysis is paramount yet challenging due to intensive computational demands. This thesis addresses this issue by introducing novel methods to operate in the compressed domain. Four methods are proposed for image reconstruction from High Efficiency Video Coding (HEVC) Intra bitstreams, namely, the Block Partition Based Method (Mbp…

Fingerprint, is considered one of the most crucial scientific tools in solving criminal cases. This biometric feature is composed of unique and distinctive patterns found on the fingertips of each individual. With advancing technology and progress in forensic sciences, fingerprint analysis plays a vital role in forensic investigations and the analysis of evidence at crime…

A large part of human speech communication takes place in noisy environments and is supported by technical devices. For example, a hearing-impaired person might use a hearing aid to take part in a conversation in a busy restaurant. These devices, but also telecommunication in noisy environments or voiced-controlled assistants, make use of speech enhancement and…