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Source apportionment of Pb in PM10 from the Upper Meža Vally by the use of advanced analytical techniques

Author(s): Tjaša Žerdoner (Author), Tea Zuliani (Supervisor), Janja Vidmar (Co-Supervisor)

Year: 2025

Type: Doctoral dissertation

Knowledge of the pollution activity at the mining and smelting sites and assessment of contamination levels at different sites is not always sufficient for reliable conclusions regarding lead (Pb) provenance and contributions from sources. Pb isotopes have long been used as ‘fingerprints’ of the source of Pb recorded in environmental …

Ecological modelling of the phytoplankton community in the northern Adriatic sea

Author(s): Ivano Vascotto (Author), Janja Francé (Supervisor)

Year: 2025

Type: Doctoral dissertation

This dissertation examines the ecological dynamics of phytoplankton communities in the northern Adriatic Sea, focusing on phenology, environmental drivers, and trophodynamics. The complexity of the region, characterized by the richness of phytoplankton communities, environmental variability and intensive human activities, is not seen as an obstacle but as an opportunity to …

Genetic variability and lead exposure biomarkers

Author(s): Neža Palir (Author), Ingrid Falnoga (Supervisor)

Year: 2025

Type: Doctoral dissertation

The thesis investigates associations between the biomarkers of lead (Pb) exposure (and mercury (Hg), where applicable) and genetic variability in in vulnerable populations, including pregnant women and their newborns from Italy, Slovenia, and Croatia, as well as Slovenian men of reproductive age. The research utilizes data from the Public Health …

Representing and exploiting benchmarking data for optimisation and learning

Author(s): Ana Kostovska (Author), Panče Panov (Supervisor), Sašo Džeroski (Co-Supervisor), Tome Eftimov (Co-Supervisor)

Year: 2025

Type: Doctoral dissertation

The rapid advancements in Machine Learning (ML) and Black-Box Optimization (BBO) have led to an increased reliance on benchmarking data for evaluating and comparing algorithms across diverse domain tasks. However, the effective exploitation of this data is hindered by challenges such as syntactic variability, semantic ambiguity, and lack of standardization. …

Identification of hearth sounds for the analysis of cardiac pathology using machine learning

Author(s): David Susič (Author), Anton Gradišek (Supervisor), Matjaž Gams (Co-Supervisor)

Year: 2024

Type: Doctoral dissertation

Cardiovascular diseases (CVDs) are a leading cause of mortality globally, significantly affecting patient quality of life and imposing considerable demands on healthcare systems. Chronic heart failure (CHF), a common outcome of CVDs, represents a growing health burden with an increasing incidence. Accurate and early identification of CVDs is critical for …

Diagnosis and prognosis of solid oxide cell systems: a statistical approach

Author(s): Luka Žnidarič (Author), Đani Juričić (Supervisor)

Year: 2024

Type: Doctoral dissertation

Hydrogen is a promising energy carrier in the emerging green energy landscape. It is environmentally friendly, transportable, and storable. The Solid Oxide Cell (SOC) system is a complex technology that enables the bidirectional conversion of hydrogen to energy. The label SOC entails solid oxide fuel cell (SOFC) systems, which produce …

Smart denoising for recurrent neural network optimization

Author(s): Jakob Jelenčič (Author), Dunja Mladenić (Supervisor)

Year: 2024

Type: Doctoral dissertation

This thesis introduces a new optimization method based on deep learning, designed for data influenced by random processes. The main contribution of this method is the combination of advanced noise reduction techniques with recurrent neural network models, which helps to prevent the common problem of overfitting seen when there is …

Strontium isotope composition: : insights into geological and environmental influences on the provenance studies of dairy products and timber

Author(s): Majda Nikezić (Author), Tea Zuliani (Supervisor)

Year: 2024

Type: Doctoral dissertation

This dissertation aimed to explore the potential of Sr isotope ratio analysis, combined with multi-elemental profiling, as a tool for geographic discrimination, focusing on two projects: tracing the provenance of cheese/milk from Naxos, Greece (Project 1), and wood in the Eastern Carpathians, Romania (Project 2). The goal was to understand …

Using machine learning methods for analyzing sequential textual data

Author(s): Erik Novak (Author), Dunja Mladenić (Supervisor)

Year: 2024

Type: Doctoral dissertation

This thesis investigates machine learning methods for analyzing sequential textual data. Sequential textual data refers to text collected in a specific order where the sequence is significant. Examples include (1) sentences, where word usage and order must adhere to the rules of grammar, (2) news reporting on events happening at …

Isotopic fingerprint of water from source to tap

Author(s): Klara Žagar (Author), Polona Vreča (Supervisor)

Year: 2024

Type: Doctoral dissertation

Rapid population growth and increasing water demand places a serious strain on both quantity and quality of available local water resources. Climate change puts additional pressure by altering the water balance, affecting recharge conditions, and contributing to pollution and water degradation. Addressing these issues requires water management strategies that enhance …