M.S. Thesis

M.S. Thesis

Gökçe Komaç, Measuring the Effectiveness of a Persuasive Game About Online Trolling in the Context of Gaming: A Case Study

In this study, ‘awareness’ and ‘knowledge’ are used as means of measurement to evaluate the effectiveness of persuasive games. A game about online trolling behavior is designed and impleted. After exploring how the toxic behaviors that are considered as trolling in the context of online gaming are perceived, this study observes if the persuasive game is effective in raising awareness and knowledge about these behaviors.

Date: 09.09.2019 / 10:00 Place: B-116

Gökçe Komaç, Measuring the Effectiveness of a Persuasive Game About Online Trolling in the Context of Gaming: A Case Study

English

Gizem Özen, The effect of kinemorphs on F-Formation shapes: an investigation on human robot interaction in virtual reality

In this study, firstly, the effect of kinemorphs on F-formation shapes are investigated by focusing on the differences between the virtual environment and the real life settings. Secondly, the role of one-to-one F-formation shapes on joining a dyadic interaction as a third interactant is also studied.

Date: 12.09.2019 / 15:00 Place: A-212

Gizem Özen, The effect of kinemorphs on F-Formation shapes: an investigation on human robot interaction in virtual reality

English

Ümit Eronat , Synthesis of Soundscapes Based on an Automatic Analysis of Auditory Imagery in Literary Texts

Our project brings together the concept of sound generation from free text input. Because a good story text can describe an environment quite well, both in terms of visual and aural aspects, we decided to use this feature to create virtual soundscapes that will both be generated procedurally and have the depth, complexity and control of a story text. In this thesis we describe the mechanics of analyzing free text user input queries and a way of converting this analysis into procedural soundscape generation.

Date: 05.09.2019 / 10:00 Place: A-108

English

Bilgin Aksoy, Perceptual Quality Preserving Adversarial Attacks

Image based CAPTCHA systems are being used to validate if the candidate user is a human or a bot. Several DNN based systems have been achieved to fail this validation process. As a result, the reliability of CAPTCHA has become controversial. Adversarial image is a sample that is intentionally modified by adding non-random noise to deceive DNNs, and recently has been used to deceive DNNs to make CAPTCHA system more reliable. But the adversarial process degrades the image quality which makes it also difficult for humans to classify images and recognize objects. The proposed method preserves perceptual quality of adversarial images and still generates adversarial images which have 100% attack accuracy.

Date: 02.09.2019 / 10:00 Place: A-212Bilgin Aksoy, Perceptual Quality Preserving Adversarial Attacks

English

Samet Albayrak , Semantic/Pragmatic Processing in Turkish Propositional Attitude Verbs: The Case of "Zannet"

Investigation of the Theory of Mind was conducted in a verbal setting. This setting is constructed with help of some cognitive propositional attitude verbs (bil, düşün, and zannet) because they are used for referring to mental states as ToM is used for inferring mental states. In addition to the evaluation of verbs, participants’ ability to process pragmatic inferences were measured and these two sets of data were investigated for any relationship between them.

Date: 09.09.2019 / 10:00 Place: A-108

English

Meriç Kınalı, Leveraging The Human Kinome for Anticancer Agent Cytotoxicity Potency Prediction

In this study, we presented a regression model, which was applied on cytotoxic bioactivity data obtained from HCC cells (from CanSyL dataset). Our objective was to predict off-target effects as potential new targets by regularizing the regression space based on the kinome tree topology. Our model was tested on the CanSyL dataset by applying LOOCV and achieved promising predictions. Then we scaled up our approach to the public datasets (CCLE and GDSC). Some kinase inhibitors were identified as outliers based on their individual RMSE. This difference suggests that outlier inhibitors are more specific inhibitors while non-outlier inhibitors are mostly multi-kinase inhibitors.

Date: 06.09.2019 / 10:00 Place: A-108

English

Oğuzcan Ergün, Developing Building Information Modelling Based Virtual Reality and Mixed Reality Environments for Architectural Design and Improving User Interactions with Serious Games

In the first part of this thesis, a BIM based architectural visualization and design tool is developed for VR, MR and PC environments. BIM provides detailed information and tools to professionals so that they can develop and manage buildings and infrastructures efficiently. In the second part of this thesis, two tutorial-like serious games, based on VR and MR environments, are developed to improve the users’ overall experience and to ease the user interactions in virtual environments. The developed tool and the serious games were tested by architects and game developers, and were evaluated from presence, usability, and technology acceptance perspectives.

Date: 29.08.2019 / 16:00 Place: A-212

English

Atıl İlerialkan, Speaker and Posture Classification Using Instantaneous Acoustic Features of Breath Signals

Features extracted from speech are widely used for problems such as biometric speaker identification, but the use of speech data raises concerns about privacy. We propose a method for speech and posture classification using only breath data. The acoustical information was extracted from breath instances using the Hilbert-Huang transform and fed into our CNN-LSTM network for classification. We also created our publicly available dataset, BreathBase, which contains more than 4600 breath instances of 20 participants in 5 different postures with 4 different microphones. Using this data, 56% speaker classification and 96% posture classification accuracy is obtained.

Date: 02.09.2019 / 11:00 Place: A-212


English

Cansu Dinçer, 3D Spatial Organization and Network-Guided Comparison of Mutation Profiles in Glioblastoma

Accumulation of genomic alterations can lead to tumorigenesis. One of the deadliest brain tumor type, Glioblastoma is well-known for its genomic heterogeneity which makes the disease as incurable. In this thesis, we aimed to decrease the heterogeneity among Glioblastoma patients from The Cancer Genome Atlas (TCGA), classify the patients and propose therapeutic hypothesis for patient groups by using patient mutation profiles. We therefore implemented a systems level approach using three dimensional (3D) spatial organization of the mutations (mutation patches), organization of mutated proteins in patient specific protein interaction networks, and drug responses of the GBM cell lines.

Date: 28.08.2019 / 11:00 Place: A-212

Cansu Dinçer, 3D Spatial Organization and Network-Guided Comparison of Mutation Profiles in Glioblastoma

English

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