Graduate School of Informatics, Thesis

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Thesis (918)

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Author
Akkoyun, Emrah (2)
Alaşehir, Oğuzhan (2)
Alkan, Sarper (2)
Alkış, Nurcan (2)
Altınışık, Said (2)

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Engineering and Technology (133)
Social Sciences and Humanities (59)
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Computer software. (33)

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1998 - 1999 (3)
2000 - 2009 (206)
2010 - 2019 (495)
2020 - 2024 (208)

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Master Thesis (695)
Ph.D. Thesis (223)

Recent Submissions

Efficient primer design for genotype and subtype detection of highly divergent viruses in large scale genome datasets Demiralay, Burak; Acar, Aybar Can; Department of Medical Informatics (2024-3-11) Identification of microorganisms is a crucial step in diagnostics, pathogen screening, biomedical research, evolutionary studies, agriculture, and biological threat assessment. While progress has been made in studying larg...
WORD INTERNAL STRUCTURE IN CHINESE: EVENT STRUCTURE, PREDICATE-ARGUMENT STRUCTURE AND CATEGORIES IN SEPARABLE VERBS Kao, Tzu-Ching; Bozşahin, Hüseyin Cem; Department of Cognitive Sciences (2024-2) The study of Chinese separable verbs has long been one of the unresolved and under-debated challenges in the field of Chinese linguistics due to their indivisible semantics, yet decomposable syntactic behaviors of separabl...
Analyzing decision making behaviour under risk and uncertainty with the help of computational cognitive modeling and neuroscience perspectives Bulur, Hatice Gonca; Çakır, Murat Perit; Department of Cognitive Science (2024-1-26) This study aims to understand individuals' decision making behaviour under risk and uncertainty by bringing insights from computational cognitive modeling and neuroscience perspectives. More specifically, it investigates c...
A GENERIC BLOCKCHAIN PROCESS REFERENCE MODEL FOR SOFTWARE DEVELOPMENT IN SAFETY CRITICAL DOMAINS Baysal, Merve Vildan; Özcan Top, Özden; Betin Can, Aysu; Department of Information Systems (2024-1-26) In recent years, blockchain technology has garnered significant interest and shown promises in various safety critical domains such as health, automotive, and energy. In safety critical domains, any failure or malfunction ...
Prediction of Covid-19 risk of a person by analyzing computed tomography images using convolutional neural networks Topçu, Kaan; Acar, Aybar Can; Department of Information Systems (2024-1-24) In this thesis, 4 main research questions are answered to evaluate the performance of convolutional neural networks (CNN) in predicting Covid-19 risk by using computed tomography (CT) images. The CT images by Yang et al., ...
CROSS-DISCIPLINARITY IN COGNITIVE SCIENCE: A DOCUMENT SIMILARITY ANALYSIS Alaşehir, Oğuzhan; Çakır, Murat Perit; Acartürk, Cengiz; Department of Information Systems (2024-1-22) Systematic quantification of cross-disciplinarity necessitates bibliometric and spatial analysis, socio-institutional aspects, or text-based techniques. Especially, with the advancement in bibliometric methods, a variety o...
Uncovering Hidden Connections and Functional Modules via pyPARAGON: a Hybrid Approach for Network Contextualization ARICI, Muslum Kaan; Acar, Aybar Can; Tunçbağ, Nurcan; Department of Bioinformatics (2024-1-22) State-of-the-art omics technologies provide molecular insights into various biological contexts, such as disease states, patients, and drug perturbations. Network inference and reconstruction methods utilize several omics ...
USING TOPOLOGICAL FEATURES OF MICROSERVICE CALL GRAPHS TO PREDICT THE RESPONSE TIME VARIATION Fındık, Barış; Günel Kılıç, Banu; Betin Can, Aysu; Department of Information Systems (2024-1-19) Microservice architectures are increasingly gaining popularity in the field of software design. Research on the topology of graphs formed by communication between microservices is a subdomain within the broader scope of mi...
Examination of institutional investor network patterns in context of major crashes in US stock markets Demirel, Ersin; Günel Kılıç, Banu; Department of Information Systems (2024-1-18) In the dynamic landscape of the stock market, accredited investors in the US are required to report quarterly holdings in their portfolios to the Securities and Exchange Commission (SEC) using Form 13F. Although these fili...
A robust machine learning based IDS design against adversarial attacks in SDN Alper, Sarikaya; Günel Kılıç, Banu; Demirci, Mehmet; Department of Information Systems (2024-1-17) Machine learning-based intrusion detection systems (IDS) are essential security functions in conventional and software-defined networks alike. Their success and the security of the networks they protect depend on the accur...
Hyperspectral Imaging Applications for Steel Production Korkmaz, Özgür; Yardımcı Çetin, Yasemin; Department of Information Systems (2024-1-11) Steel production is the backbone of numerous infrastructure projects and industrial applications around the world. To maintain and improve its productivity, quality, and environmental sustainability, the steel industry is ...
Development of a maturity index for digital transformation in organizations Şener, Umut; Eren, Pekin Erhan; Gökalp, Ebru; Department of Information Systems (2024-1) Organizations aim to maximize the benefits of digital transformation (DX) by deploying connected, intelligent, and self-governed systems that leverage diverse technologies, such as the Internet of Things (IoT). In order to...
Exploring user experience and perceptions of a location-based augmented reality game: the case of METU Discover Altınsoy, Zafer; Kaplan, Göknur; Department of Modeling and Simulation (2024-1) Location-based games use real-world location as a fundamental element of gameplay, potentially influencing players' relationships with their surroundings. This thesis aims to understand user experience and perceptions of a...
Development of a Decision-Support Tool for Managing Drinking Water Reservoir by Using Machine Learning and Deep Learning Methods Özdemir, Serkan; Özkan Yıldırım, Sevgi; Yaqub, Muhammad; Department of Information Systems (2023-12-19) Global climate change has led to large fluctuations in lake levels in recent years, due to both changing meteorological parameters and intensive water use. A shift in input or output variables can easily alter the water ba...
PREDICTING MANIPULATION ATTEMPTS BY STUDENTS ON LEARNING MANAGEMENT SYSTEMS: AN APPROACH USING MACHINE LEARNING MODEL Görmezoğlu, Mehmet Melih; Yıldırım, İbrahim Soner; Özkan Yıldırım, Sevgi; Department of Information Systems (2023-12-18) This study focuses on the identification of students' behavior, spanning from 1st grade to 8th grade, within a designated Learning Management System, specifically aiming to detect potential instances of attempting to "game...
Predicting tennis match outcome: a machine learning approach using the SRP-CRISP-DM framework Ünal, Toyan; Özkan Yıldırım, Sevgi; Department of Information Systems (2023-12-07) Machine learning methods have demonstrated effectiveness in forecasting tennis match results. However, due to their empirical nature, decisions regarding the choice of specific datasets, models, feature sets, or hyperparam...
Development and Validation of Artificial Intelligence-Based Recruitment Acceptance Model: An Empirical Investigation Among Candidates Aydemir, Büşra; Özkan Yıldırım, Sevgi; Department of Information Systems (2023-12) The utilization of artificial intelligence (AI) technologies in various areas rising exponentially year by year and is expected to continue its growth in the future. Human resources (HR) function is one of the areas that...
PREDICTING THE PRIMARY TISSUES OF CANCERS OF UNKNOWN PRIMARY USING MACHINE LEARNING Karimov, Kamran; Acar, Aybar Can; Department of Bioinformatics (2023-12) Cancers of Unknown Primary (CUP) origin are metastases where the primary source of the tumor cannot be detected and only the secondary tumor is evident. This can cause problems in treatment since the tissue of origin defin...
BIBLIOMETRIC ANALYSIS OF FUNCTIONAL NEAR-INFRARED SPECTROSCOPY (FNIRS) IN NEUROIMAGING LITERATURE Koçak, Murat; Çakır, Murat Perit; Korkusuz, Feza; Department of Medical Informatics (2023-9-11) This thesis study aims to explore the Functional Near Infrared Spectroscopy (fNIRS) literature by utilizing bibliometric analysis techniques. In particular, we aimed to investigate the interdisciplinary nature of the fNIRS...
Species Classification from Short Genomic Reads using Feedforward Neural Networks Özzeybek, Emre; Acar, Aybar Can; Department of Bioinformatics (2023-9-11) With the cost of Next Generation Sequencing technologies in decline, the need for fast and efficient classification of genomic findings has become of utmost importance. Due to the output length limitations of most Second G...

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