M.S. Thesis

M.S. Thesis

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

Müge Değirmenci Camcı, Synthesis of Realistic 3D Artifacts Using Flow Fields

There is a high demand for realistic computer aided imagery by many applicatiion areas such as games and movies. Due to the complicated characteristics of certain natural phenomena such as fire, smoke or mist, it is difficult to realistically mimic these effects. There are various approximation methods to visually synthesize lifelike 3D artifacts. The use of flow fields to guide the motion of particles creates a random but natural-looking effect. The aim of this study is to use flow fields to generate realistic 3D visual effects.

Date: 06.09.2019 / 11:00 Place: A-212

Müge Değirmenci Camcı, Synthesis of Realistic 3D Artifacts Using Flow FieldsMüge Değirmenci Camcı, Synthesis of Realistic 3D Artifacts Using Flow Fields

English

Selahattin Polat, Performance Evaluation of Lightweight Cryptographic Algorithms for Internet of Things Security

In this thesis, we investigated the suitability and adaptability of the lightweight cryptographic algorithms on IoT devices, and compare their implementations with those of standard algorithms. We realized our implementations on the Arduino Uno platform, which is widely used in several embedded applications and preferred as a target development platform for its low price-performance ratio. We mainly focused on block ciphers and hash functions, which are the fundamental components of many cryptographic protocols. Among these protocols, Internet Protocol Security (IPSec) suite and DTLS are perhaps from the most well-known and commonly used ones. With our study, we plan to provide results that may be guidelines for existing and future lightweight implementations of IPSec, DTLS and other security protocols on IoT devices.

Date: 26.07.2019 / 13:00 Place: A-212

English

Elif Bozlak, De Novo Snp Calling and Demographic Inference Using Trio Genome Data

In this thesis, we aim to analyze NGS data of three different domestic horse families to detect de novo mutations that occur within one generation. We found a higher number of true positives in highly covered data, while a lower number of true positives in the low covered data, showing the importance of sequencing coverage to detect true de novo mutations. In addition, to make estimations on the demographic history of the families we made PSMC and ROH analysis. Results of these analyses were coherent with previous studies. All in all, we had an idea for the minimum coverage threshold and quality of whole-genome sequencing data, to determine de novo mutations and to estimate population demography.

Date: 29.07.2019 / 11:00 Place: A-212

English

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