Graduate School of Informatics /Information Systems

In partial fulfillment of the requirements for the degree of Master of Science Alper Sarıkaya will defend his thesis.

Title: ANOMALY-BASED CYBER INTRUSION DETECTION SYSTEM WITH ENSEMBLE CLASSIFIER

Date: 06th September 2018

Time: 14:00 PM

Place: A-212

Thesis Abstract : Nowadays, cyber attacks are beginning to occur at an increasing rate. Along with this, diversity, size and density of the cyber attacks are increasing accordingly. When we analyze log in the security devices, we find that the massive amount of attacks sign was created. Besides, It is also difficult for human to evaluate the log accurately. Therefore, the identification of key data, which can be used to distinguish attack from this very large data set, is important for both rapid detection of attack and rapid response of security devices. In this study, we will focus on selection of appropriate data from the log via machine learning and determine the distinctive attributes specific to the attack in the selection of these data. Thus, we will research on the classification of the data to be used in the attack detection via machine learning.

Title: APPLICATION OF BINARY PSO TECHNIQUE FOR THE SOLUTION OF MATHEMATICAL MODELLING OF PUBLIC CLOUD RESOURCES ALLOCATION SYSTEM FOR VIDEO ON DEMAND (VOD) APPLICATIONS

PhD Candidate: Betül Aygün

Program: Informations Systems Department 

Date: 03 September 14:00

Place: Conference Hall-01

Abstract: Video streaming services whether on demand or live has become one of the most popular services used recently. However, investments made for these type of applications cause a very serious financial problem just because video type of multimedia data needs more real time storage and high data transfer than other type of multimedia data. Furthermore, for the video streaming applications, significant amount of system resource in computing is required. To tackle this problem, cloud computing emerges as a preferred technology. Cloud services organizations are becoming more and more sophisticated as they enable the organizations to offer services without investing in hardware or software. A huge number of cloud service providers offer different pricing methods for various applications in various regions. For this reason, it is of great importance that incoming service requests are assigned to appropriate cloud services with minimum cost and maximum user satisfaction (QoS). Because of issues like multiple cloud providers, different quality of service requirements, different service level agreements (SLA) and uncertainties in demand, price and availability, optimization of resource allocation has some challenges. The objective of this study is to optimize the cost and performance of video on demand services using cloud CDNs, storage and transcoders based on QoS requirements of users. In this paper, Mixed Integer Quadratic Programming (MIQP) and different variants of Particle Swarm Optimization (PSO) algorithm are used to schedule video requests to cloud resources to achieve minimum cost of cloud services and maximum of user satisfaction. Due to the nature of the problem, it is not possible to use the classic PSO, but the new algorithms which combine Binary PSO with heuristics algorithms are proposed. These algorithms are compared with LP algorithms which gives best result. The results show that proposed algorithms yield better results than the benchmarking algorithms.

Graduate School of Informatics / Bioinformatics

In partial fulfillment of the requirements for the degree of Master of Science Tuğba Kaya will defend his thesis.

Title:STRUCTURAL MAPPING AND NETWORK ANALYSIS OF PATIENT-SPECIFIC MUTATIONS IN GLIOBLASTOMA

Date: 27th August 2018

Time: 14:00 PM

Place: A-212

Thesis Abstract :Cancer is one of the most common cause of death worldwide. It occurs as a result of a collection of somatic deviations from normal state. Therefore, many efforts has been invested to profile mutations in different types of tumors; such as, the Cancer Genome Atlas (TCGA) which deposits multiple omic data for more than 11,000 tumor samples. In this thesis, we present a pipeline which retrieves patient-specific mutation data in Glioblastoma from TCGA, maps these mutations on the protein structures in Protein Databank (PDB) and finds the location and functional effect of the mutations and reconstruct functional networks by integrating mutation data with interactome. As a result of this thesis study, we found that some mutations are specific to alternative isoform sequence of the protein instead of the canonical sequence. We also showed that functional impact of mutations in interface region is more damaging compared to the surface region and more similar to the core region of the protein. We showed that most common change in the protein core is that hydrophobic residues are mutated to another hydrophobic residue. However, in the surface or interface region a charged residue is changed either to another charged residue or a polar residue when we analyzed the chemical classes of mutations. From these mutation profiles of the patients, we reconstructed 290 GBM-specific networks with Omics Integrator which solves the prize-collecting Steiner forest (PCSF) problem and optimally connects the given set of proteins in a network context. We merged the most common nodes and edges across these patients and clustered the merged network into functional communities. The ontology and pathway enrichment analyses gave us that Wnt signaling, ERBB signaling and NfKb/Ikb signaling pathways are the most commonly enriched pathways. From mutation to protein structures and functional networks, we believe that the result of this thesis will have significant contribution in cancer research.

Graduate School of Informatics /Information Systems

In partial fulfillment of the requirements for the degree of Master of Science Ayşe Begüm Kılıç will defend his thesis.

Title: INVESTIGATING THE TRANSFORMATION OF SUPPLY CHAINS INTO DIGITAL SUPPLY CHAINS BY USING SOFT SYSTEMS METHODOLOGY: A CASE STUDY

Date: th August 2018

Time: 13:30 AM

Place: A-212

Thesis Abstract :Currently, Industry 4.0 is trending topic among researchers. Basically, it promises firms higher profits by using technologies that are more advanced. In order to benefit from Industry 4.0, digitization of all company operations is essential for companies. That is why today, examining the transformation into the digital world has a significant role for the future. This thesis aims to investigate the transformation of supply chains into digital supply chains (DSC) in firm level by using Soft Systems Methodology (SSM). SSM enables researchers to analyze and define a problem to find out its real causes and suggest changes to solve it. SSM does not require quantitative data for analysis and is suitable for not fully defined and not well-known problems. Since the changes in the shifting from regular supply chains to DSC are not defined with numeric data and it is hard to define all the expected transformation clearly, the SSM methodology is chosen to follow. A case study applied to a firm will be conducted via interview technique within the thesis. The SSM is expected to be beneficial on analyzing the subjective data that will be provided by these interviews. At the end of the thesis, it is predicted to define the real-world transformation process and offer suggestions to firms in order to cope with the change

Graduate School of Informatics /Information Systems

In partial fulfillment of the requirements for the degree of Master of Science Güliz Bulut will defend his thesis.

Title: AUTOMATIC INFORMATION COVERAGE ASSESSMENT OF DIABETES WEBSITES

Date: 3rd September 2018

Time: 10:00 AM

Place: A-212

Thesis Abstract :People frequently access Internet to look up health information. However, as the quality of websites may vary significantly, the treatment recommendations and guidelines provided by some of these web sites may be fallacious. Consequently, patients may unfollow their current treatments suggested by their doctors or start following unfounded treatments. In this thesis, an automated approach is presented to estimate information coverage of websites. The approach is based on a domain-dependent standard knowledge base (KB) and enhanced by open source resources. Elastic net regularized regression is used to construct a model for estimation. As a case study, corpus of type 2 diabetes related web pages is selected. “Standards of Medical Care in Diabetes” published by American Diabetes Association is processed to obtain factual data about treatment of type 2 diabetes. This standard serves as a detailed knowledge base on type 2 diabetes treatment and enables to produce a trustworthy input for evaluation. In light of this KB, the corpus of type 2 diabetes related web pages is processed to retrieve their coverage of factual information. It is observed that, extracting significant terms from a domain-dependent knowledge base provide a basis to measure information coverage of a source

Title: TRANSFER AND MAINTENANCE EFFECTS OF N-BACK WORKING MEMORY TRAINING IN INTERPRETING STUDENTS: A BEHAVIOURAL AND OPTICAL BRAIN IMAGING STUDY

PhD Candidate: Asiye Öztürk

Program: Cognitive Science Department 

Date: 29 August 13:00

Place: Conference Hall-01

Abstract:Working memory training is seen as an effective tool for enhancing performance during a variety of high level cognitive tasks for different groups such as children, older people, and individuals with cognitive problems as well as practitioners of highly cognitive demanding professions. Although there has been some controversy regarding the efficiency of working memory training interventions, it has been shown that n-back working memory training results in improvements in working memory capacity as well as in reasoning skills which points out that it yields both near and far transfer effects. Considering the crucial role of working memory in interpreting profession, this thesis targeted interpreting students in order to investigate transfer and maintenance effects of n-back working memory training through a comprehensive analysis of its near, moderate and far transfer effects as well as possible transfer to consecutive interpreting. Combining behavioural data collection methods and fNIRS (functional near-infrared spectroscopy) as an optical brain imaging technique, the thesis was designed as a longitudinal study in which participants completed a series of tests before and after the training as well as three months after the completion of the training sessions. Compared to an active control group, n-back group had larger performance gains in near and far transfer tasks, and more importantly in consecutive interpreting scores as a result of enhanced working memory capacity, suggesting that common working memory processes are employed in the tasks. Significant neural activity patterns observed in prefrontal cortex reflect the shared cognitive processes of n-back training and consecutive interpreting, which is supported by performance improvements in consecutive interpreting and increased neural efficiency. Therefore, it is believed that findings of this thesis will have original contributions to the field.

Graduate School of Informatics /Cognitive Sciences

In partial fulfillment of the requirements for the degree of Master of Science Ayşenur Hülagü will defend his thesis.

Title: THE FUNCTIONALITY OF NON-VISUAL GAZE PATTERNS DURING REMEMBERING OF THE PAST AND IMAGINING THE FUTURE: EVIDENCE FROM EYE TRACKING

Date: 2nd August 2018

Time: 13:00 AM

Place: B-116

Thesis Abstract :Future-oriented thoughts play an important role in human mental life. They can be more or less abstract, including themes such as work, relationships, leisure activities and errands, and serve functions such as action planning, decision making and emotion regulation (d’Argembeau et al., 2011). Future-oriented thoughts share some properties with past memories. Both can comprise episodic as well as semantic aspects. Episodic cognition is the capacity for mental time travel and allows a person to relive and prelive events of their own life (Suddendorf et al., 2009) whereas semantic cognition is related to general world knowledge. According to Szpunar et al. (2014), there seems to be a whole continuum of episodic and semantic forms as well as different modes of future thinking such as simulation, prediction, intention, and planning, serving different functions for adaptive behavior. An important but as yet unresolved empirical issue is how one can distinguish episodic and semantic forms of past and future cognition, respectively. Micic et al. (2010) revealed in three experiments that non-visual gaze patterns occur frequently during mental activities, in particular during long-term memory searches. Non-visual eye-movements may therefore indicate mental simulation during remembering the past, which is characteristic of episodic cognition. In this study eye-tracking methodology will be used to find out whether non-visual gaze patterns occur during thinking of the past and into the future and, if so, whether they may be diagnostic of episodic as compared to semantic thinking.

Title: COGNITIVE, PERCEPTUAL-MOTOR AND SOCIAL FACTORS IN TOOL MAKING IN CHILDREN

PhD Candidate: Gökhan Gönül

Program: Cognitive Science Department 

Date: 10 July Tuesday15:30

Place: Conference Hall-01

Abstract:Making tools and using tools expertly has been considered as one of the most distinctive abilities of humans. However, pre-school children are not proficient in every aspect of tool-related behaviors, in particular tool making. The cognitive, perceptual-motor and social factors in the tool making in children have been disregarded by researchers hitherto. Considering the cognitive and social abilities of humans, this thesis aims to provide a new way of looking at human tool making. In addition, it is aimed to find facilitative factors in the process of tool making.

Title: ESSENTIAL DESIGN COMPONENTS OF GENETIC DATA ENABLED MOBILE PERSONAL HEALTH RECORD SYSTEMS

PhD Candidate: Özlem Özkan

Program: Health Informatics Department 

Date: 09 July Monday 09:30

Place: Conference Hall-01

Abstract:The rapid growth in the use of genetic tests in healthcare has opened a new discussion on redesign of electronic health records to cover the genetic/genomic data. Today, this work is done in the same way with ordinary health data. However, genetic data has many unique properties that raise concerns on privacy and security issues and there are even special laws and acts to protect genetic/genomic in many countries. We strongly suggest Personal Health Records (PHR) systems for this purpose since it is under full control of the owner, and so has a great potential to cover privacy concerns. Thus, we applied four sub-studies in order to identify critical design issues of genetic data enabled mobile PHR in the scope of this dissertation. First, we analyzed the mobile application markets and evaluated the mPHRs in order to see what is in existing applications, and to identify the missing aspects. Second, with the help of the analysis results, a survey was developed and conducted to 174 people, half of which had genetic test experiences to reach publics concerns and views on the issue. Third, as a parallel study, 11 participatory design sessions with five participants were held and a paper prototype of genetic data included mPHR was developed as a result. Lastly, two focus group studies on collection of genetic data and confidentiality in Turkish health information systems were organized with 18 experts. By this way, all aspects of a genetic data enabled mPHR design were determined and presented to the literature.

Graduate School of Informatics /Cognitive Science

In partial fulfillment of the requirements for the degree of Master of Science Aysel Yasemin Göl will defend his thesis.

Title: AN EXPERIMENTAL INVESTIGATION OF CHANGE BLINDNESS BY GROUP EYE TRACKING PARADIGM

Date: 01th June 2018

Time: 10:00 AM

Place: A-108

Thesis Abstract :The group effect refers to a decline in vigilance when an individual is in a social, group setting. Due to a diluted risk of being preyed upon and a higher number of group members that can detect a predator, members are less alert when they are in a group. The present study investigates if such an effect can be observed in human participants in a simple change detection task by employing group eye tracking (GET) paradigm. For this end, the visual phenomenon of change blindness is explored. In a within-subjects experiment, participants attempted to find if a change has been made to a stimulus they have previously seen. The same task was performed twice, once alone and once in a group of three while their eye movements were recorded with an eye tracker. Results of eye movement analysis show that, during the visual search for a change, eye movements are significantly slower when the participants are in groups (p < .01). The findings indicate that this effect may be related to a decline in vigilance and the group effect.