Graduate School of Informatics

This study aims to gain an understanding of the content and the epistemic causal connective acquisition process of children aged 6;5- 8 in Turkish. For this purpose, to test whether there are connectives that children use specific to domains of causality as adults do (Çokal, Zeyrek, & Sanders, 2020); child and adult participants are given both descriptive (biased for content relations) and argumentative (biased for epistemic relations) tasks. Data that is collected from these tasks are annotated and statistically analyzed.

Date: 27.04.2023 / 15:30 Place: A-212

Hepatocellular carcinoma (HCC) is a type of primary liver cancer that is highly lethal and needs better treatment options. The thesis identifies several drugs and drug combinations that show promise in targeting drug-resistant HCC cells and cancer stem cells based on in silico modeling and in vivo experiments. It found that a combination of Sunitinib and Chloroquine Phosphate is synergistically cytotoxic on HCC cells, while novel isoxazole-piperazine compounds also show bioactivities against HCC cells and cancer stem cells. The study presents significant findings that highlight the potential of repurposed drugs and novel compounds as drug candidates for HCC.

Date: 24.04.2023 / 10:30 Place: A-212

This thesis contributed to the edge computing literature by providing the first sectoral edge computing technology roadmap. It identifies how the focus of edge computing research changes by the application domain and objectives. Market and technology trends are discovered with dynamic topic modeling, using LDA and BERTopic methods. Technology roadmapping literature is extended by integrating data layer in a data-driven technology roadmap for social change and technology forecasting.

Date: 17.04.2023 / 13:00 Place: A-212

In this study, by using facial images and EMG recordings, a novel assessment method based on computation will be developed. The method to be developed will be quantified, repeatable, and easy to run autonomously on a regular computer or device.

Date: 07.04.2023 / 11:00 Place: A-212

This study investigates pronominal anaphora in a Turkish and English translated TED corpus, the TED-MDB (Zeyrek et al., 2020), and provides a heuristic-based resolution mechanism for each language. The corpus comprises 364 English-Turkish sentences aligned. Research has two phases. The annotator annotated the data in the first phase. In the second phase, the knowledge poor method of Mitkov (1998) was tested on the Turkish and English annotated corpuses independently. TED presentations can identify pronominal anaphora with an F1-score of 0.61 in English and 0.63 in Turkish.

Date: 27.01.2023 / 15:00 Place: A-212

In this thesis study, we focus on the construction of an effective network architecture, for which we propose an architecture generation framework and show how it can be used to create an effective terrain classification model. Additionally, we also observe that land cover training data sets on HSI and LiDAR tend to come short in providing training examples with shadow effects. To address this limitation, we additionally propose a generative adversarial network(GAN) driven statistical data augmentation technique that generates synthetic training examples and show its effectiveness in our experimental results.

Date: 26.01.2023 / 14:30 Place: A-108

Among various Agile Software Development methods, Scrum is one of the most widely adopted one. The Scrum Guide clearly describes the Scrum events, artifacts, and roles. However, due to various project characteristics such as team size, team distribution, project domain, technology and requirement stability levels, Scrum practices need to be tailored. In this thesis, we analyze the various adaptations and tailoring choices of companies using Scrum. By incorporating evidence from literature and a survey study that is conducted among participants who use Scrum in their organizations, the impact of Scrum tailoring on technical debt will be analyzed.

Date: 24.01.2023 / 15:00 Place: B-116