Graduate School of Informatics

Most of the variants in the genome are at the non-coding region. While variations in the coding region effect the protein, variations in non-coding region effect the regulatory mechanism. Therefore, observation of non-coding variations may ensure to identify variations that effect gene expression. eQTL is a popular method used for the purpose to determine the SNPs that effect the gene expression. We have implemented a python based, easy-to-use tool to understand the relationship between the somatic SNPs and gene expression based on eQTL analysis.

Date: 11.09.2023 / 14:00 Place: A-212

Crude oil prices are very volatile as they depend on many factors. Traders in this market, therefore need to constantly monitor different factors affecting the price, which can lead to information asymmetry for individual traders. Therefore, this thesis presents a comprehensive decision support system incorporating fundamental, technical, and sentiment analysis to support the decisions of crude oil traders.

Date: 06.09.2023 / 15:30 Place: A-212

Traditionally, football coaches make this decision by analyzing players' match and training performances and by analyzing the data of the opposing team. In this thesis, a new solution to the team selection problem is proposed with a data-driven approach by using the match data of the players and teams, grouping the players based on their positions and roles, considering the opposing team, tactical formation and environmental factors.

Date: 05.09.2023 / 13:00 Place: A-212

The study aimed to classify task difficulties using wavelet transform images of EEG signals and deep learning models. The EfficientNet-B0 model achieved the highest accuracy, but its performance varied significantly across individuals and task difficulties, indicating limited generalizability. The study suggests a need for further research to improve model generalizability, optimize performance, and validate the models on larger, more diverse datasets.

Date: 06.09.2023 Place: MODSIMMER Meeting Room

New technologies in distributed energy systems offer solutions for managing demand and generation variability in the grid. Trade between small grids allows cost reduction and system flexibility. This thesis proposes Multi-Agent Reinforcement Learning model for short-term energy trading among peers. It integrates short-term forecasts for load, generation, and price, leading to more accurate decision-making. Real-world data simulations demonstrate improved efficiency and stability compared to rule-based agents. This approach empowers prosumers to respond effectively to dynamic energy markets, enhancing grid reliability, energy efficiency, and sustainability.

Date: 07.09.2023 / 11:30 Place: -

In this study, changes in neural activation during joint action were investigated with hyperscanning, using functional near infrared spectroscopy (fNIRS) and electroencephalography (EEG) as participants performed the same task individually and then collaborated as a dyad. 62 participants were tested in dyads with a dual n-back task. Results are in support of the social facilitation model, and neural measures including hyperscanning were successful to differentiate between individual and social task settings. Overall, this study is one of the first studies to conduct EEG and fNIRS-hyperscanning during a complex collaboration task that brought together temporal constraints and elements of visuospatial reasoning.

Date: 05.09.2023 / 11:00 Place: A-212

Despite the high mortality and morbidity rates associated with alcohol use disorder (AUD) worldwide, the incomplete understanding of its complex molecular mechanism is the biggest limitation in providing successful treatments to patients. Monozygotic twin studies have found that AUD is about 50-60% heritable, and they have also revealed that environmental factors and epigenetic mechanisms play a role in the etiology of this disorder. In this study, we investigated excessive alcohol consumption related DNA methylation changes in four brain regions and blood in wistar rats to contribute to understanding to the understanding of the etiology of AUD.

Date: 04.09.2023 / 09:30 Place: B-116

This study aims to provide a bibliometric map of Functional Near Infrared Spectroscopy (fNIRS), a growing research area worldwide, in terms of interdisciplinary and institutional collaboration. Interdisciplinary and institutional collaborations are increasingly encouraged by universities as they have a high academic citation impact. In this study, the number of articles, number of citations, CNCI and IREW percentage in the field of fNIRS from 1980 to 2020 were analysed. Interdisciplinary and university & country collaborations that can increase these academic indicators are analysed from a bibliometric perspective.

Date: 11.09.2023 / 10:30 Place: -

This PhD thesis delves into the impact of selective directional auditory attention on eye movements and pupil responses. Concentrating on single-ear stimuli is shown to enhance attentiveness and task performance. The research explores effects of multi-talker speech interference, age, gender, and audio direction on eye movements and pupil dilation. Notably, interference influences pupils, prompting gaze shifts toward sound sources and larger pupils during competing speakers. This underscores the study's significance. These findings highlight the value of eye movement patterns and pupillometry in understanding auditory attention nuances. The implications are profound, benefiting hearing aid technology, communication for autism spectrum disorder and hearing-impaired individuals. The study also uncovers links between speech quality, word familiarity, and emotional connotations on pupil responses, contributing to a comprehensive comprehension of auditory processes.

Date: 06.09.2023 / 10:00 Place: A-212

This study explores the transformative potential of virtual reality in laparoscopic surgical training. Traditional box trainer implemented as a VR simulation, eliminating the need for physical tools and improved with incorporating feedback from surgeons and participant questionnaires. Results revealed that the VR version, equipped with tutorials, haptic feedback, and assisted grabbing physics, was more usable and accepted. Kinematic analysis showed similarities to physical training, and physiological monitoring revealed increased heart rate and reduced heart rate variability during tasks. This multimodal approach highlights VR's potential to enhance laparoscopic surgical skill development, providing an immersive and realistic training experience.

Date: 01.09.2023 / 10:00 Place: A-212