• Machine learning approaches for internet of things based vehicle type classification and network anomaly detection 

  Kolukısa, Burak (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  This thesis presents innovative approaches in the realms of Intelligent Transportation Systems (ITS) and Network Intrusion Detection Systems (NIDS) within the Internet of Things (IoT). Leveraging IoT technologies, a low-cost, ...

• Analysing network traffic and detecting network threats by using the algorithms of machine learning 

  Küçükkoç, Abdurrahman (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  As information technologies progress, the possibilities of access to information increase and therefore it becomes difficult to ensure the security of information. Today, with the use of information systems in all areas ...

• Machine learning methods for detecting genetic and infectious diseases 

  Işık, Yunus Emre (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  Completion of the whole human genome in the 2003 has led to various advances in many fields, particularly in biology, genetics, health sciences, treatment, and pharmacology. In the following years, spread of faster and ...

• Deep learning models for traffic volume prediction 

  Çini, Nevin (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  In the last 50 years, with the growth of cities and increase in the number of vehicles and mobility, traffic has become troublesome. As a result, traffic flow prediction started to attract attention as an important research ...

• Diagnosis of coronary artery disease with machine learning approaches 

  Halıcı, İkram (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  The World Health Organization states that Coronary Artery Disease (CAD) ranks as a primary cause of recorded fatalities. CAD occurs as a result of the blockage of coronary artery vessels, which are located on the surface ...

• Investigation and improvement of the smooth mode transition technique for quasi-single-stage four-switch buck-boost inverter 

  Keskinkılıç, Ebubekir (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  In recent decades, given the world's inevitable energy scarcity, increasing energy demand and green energy concerns, high efficiency energy conversion has become more important and attractive than ever, and researchers ...

• Heuristic vectorized learning method based PV forecasting by using image recognition-based sky camera integration within sensor set 

  Yavuz, Levent (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  In order to ensure the continuity of demand and production balance, the use of renewable energy resources (RES) by countries will increase in the near future. Solar power generation is important for the integration of ...

• OPTICAL SCATTERING BASED RANDOM FOREST ASSISTED PARTICLE DETECTION AND CLASSIFICATION 

  Genç, Sinan (Abdullah Gül Üniversitesi / Fen Bilimleri Enstitüsü, 2023)

  Microplastics, tiny plastic particles with sizes smaller than 5 mm., are often found in oceans, rivers, lakes, and atmosphere due to plastic pollution. Microplastics releasing toxic chemicals threaten the environment and ...

• Histopathology image classification: highlighting the gap between manual analysis and AI automation 

  Doğan, Refika Sultan; Yılmaz, Bülent (FRONTIERS MEDIA SA, 2023)

  The field of histopathological image analysis has evolved significantly with the advent of digital pathology, leading to the development of automated models capable of classifying tissues and structures within diverse ...

• Developing high brightness quantum dot led devices 

  Biçer, Ayşenur (Abdullah Gül Üniversitesi / Fen Bilimleri Enstitüsü, 2023)

  Optoelectronic devices are essential components of optical communication systems, internet and displays. Among these devices, in the category of light emitting diodes (LED), there are quantum dot LEDs (QLED) that emit ...

• Skin cancer detection and classification from dermatoscopic images using deep learning methods 

  Kalaycı, Serdar (Abdullah Gül Üniversitesi / Fen Bilimleri Enstitüsü, 2023)

  Early detection of skin cancer is crucial for successful treatment and improved patient outcomes. The most prevalent form of cancer is skin cancer and if left undetected, it can spread and become more difficult to treat. ...

• Adaptive online torque sharing function to mitigate torque ripple in switched reluctance motors 

  Genç, Ufuk (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  Electrical machines play a crucial role in modern society by transforming electrical energy into mechanical energy and vice versa. These machines include various types of motors and generators, which are used in a wide ...

• Computer aided detection of cancer using histopathology images 

  Yengeç-Taşdemir, Sena Büşra (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  Detecting colon adenomatous polyps early is crucial for reducing colon cancer risk. This thesis investigated various deep learning approaches for computer-aided diagnosis of colon polyps on histopathology images using deep ...

• Image processing based analysis and quantification of micro biomaterials and cells for biochip 

  Çelebi, Fatma (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  Quantification of tumor cells is essential for early cancer detection and progression tracking. Multiple techniques have been devised to detect tumor cells. In addition to conventional laboratory instruments, several ...

• Accelerating computer algorithm by using GPU 

  Yalçın, Salih (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  Travelling Salesman Problem (TSP) is one of the significant problems in computer science which tries to find the shortest path for a salesman who needs to visit a set of cities and it involves in many computing problems ...

• Antimicrobial peptide activity prediction using machine learning methods 

  Söylemez, Ümmü Gülsüm (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  Antimicrobial peptides (AMPs) are considered as promising alternatives to conventional antibiotics in order to overcome the growing problems of antibiotic resistance. Computational prediction approaches receive an increasing ...

• Blockchain based peer-to-peer energy trading applications 

  Seven, Serkan (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  This thesis explores the potential of innovative peer-to-peer (P2P) energy trading schemes for virtual power plants (VPPs) using blockchain technologies, smart contracts, and decentralized finance (DeFi) instruments. ...

• A reliable and secure communication design for underwater sensor networks concerning energy efficiency 

  UYAN, Osman Gökhan (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2023)

  Underwater Acoustic Sensor Networks (UASNs) recently attract scientists because of its wide range of applications and emerging technology. A design challenge in UASN's is the limited network lifetime and poor reliability ...

• An autonomous heterogeneous multi-robot system design for early fire detection 

  Serin, Ömer Faruk (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022)

  The usage of autonomous multi-robot systems for human life-endangering applications is emerging. Early wildfire detection and firefighting are two example applications. In this study, a heterogenous multi-robot system is ...

• Developing deep learning models for protein structure prediction 

  Görmez, Yasin (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022)

  The three-dimensional structure of a protein provides important clues about the function of that protein. Although there have been many studies on protein structure prediction, the problem has still not been solved completely. ...

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