• Systematic design optimization and implementation of line-start synchronous reluctance machine for down-hole submersible water pump applications 

  Tekgün, Didem (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2022)

  Considering the electric drive systems constitute roughly 40% of global energy production, improving electric machine efficiencies provides important nationwide and global scale advantages. Among the electric motors used ...

• High-energy cosmic and gamma radiation measurement with remote-controlled secondary emission ionization calorimetry modules 

  Paran, Nejdet (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  The demand for precise, robust, and reliable radiation-resistant particle detectors and ionization calorimeters intensifies, due to the escalating luminosity and unprecedented radiation conditions at particle colliders and ...

• Design and development of machine learning models for disease prediction and biomarkers detection 

  Temiz, Mustafa (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  In medical science, the prediction of diseases and the identification of biomarkers play an important role in the diagnosis and treatment of various health conditions. The recent proliferation of data mining techniques has ...

• Enhancing breast cancer detection with a hybrid machine learning approach 

  Etcil, Mustafa (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  According to the World Health Organization (WHO), breast cancer is one of the most prevalent illnesses, with 7.8 million instances recorded in the previous five years. As such, it poses a serious threat to world health. ...

• Development of a machine learning-based system to identify disease biomarkers from human gut microbiota 

  Koçak, Ayşegül (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  The human gut microbiota consists of a diverse ecosystem of organisms, encompasses billions of species. Recently developed next-generation sequencing methods have enabled researchers to examine the microbiota in greater ...

• Tree-net: Bottleneck feature supervised network for biomedical image segmentation 

  Demirci, Orhan (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  In this thesis, we introduce Tree-NET, a novel approach for medical image segmentation utilizing bottleneck feature supervision. This method enhances traditional segmentation algorithms by keeping supervision between ...

• Machine learning based network anomaly detection 

  Hacılar, Hilal (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  Intelligent technologies have led to a significant rise in internet users and applications. However, this rise in internet usage has also brought serious security challenges. Organizations rely on Network Intrusion Detection ...

• Design and implementation of nanophotonic architectures using smart-self assembly of colloidal nanomaterials 

  Şenel, Zeynep (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  DNA-driven self-assembly techniques offer precise control over the positioning of colloidal nanoparticles through specific Watson–Crick interactions, and its reversibility via controlling the temperature of medium. This ...

• Design and performance enhancement of an ultra wideband vivaldi antenna 

  Güzelkara, İzzet (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  Ultra-wideband technology has become a trending topic in the academic community since 2002 due to the release of the spectral mask by Federal Communications Commission, allowing the use of 3.6-10.1 GHz band for commercial ...

• Decentralized electronic health record management system and disease prediction with machine learning methods 

  Dedetürk, Beyhan Adanur (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  Electronic health records (EHRs) are vital to the advancement of healthcare and can help detect and prevent diseases early. However, EHR sharing faces challenges such as managing large data volumes, ensuring data privacy, ...

• Detection and classification of flaws from ultrasonic tomography images of composite materials based on deep learning 

  Gülşen, Abdulkadir (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  This thesis introduces novel methodologies for enhancing defect classification and characterization in advanced composite materials by leveraging state-of-the-art machine learning (ML), deep learning (DL), and federated ...

• Time distributed classification of alzheimer's disease on MRI scans 

  Dündar, Mehmet Sait (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  This thesis presents a comprehensive framework for studying Alzheimer's Disease (AD) progression by focusing on the classification of AD, Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) individuals using ...

• Tumor detection in breast cancer histopathological images using convolutional neural networks 

  Şahbaz, Zeki (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  Breast cancer is one of the most common cancer types among women worldwide. Early detection significantly increases the chances of survival and effective treatment, making advancements in diagnostic methodologies crucial. ...

• Perception estimation and torque control for hand prostheses using EEG and EMG signals 

  Karakullukcu, Nedime (Abdullah Gül Üniversitesi, Fen Bilimleri Enstitüsü, 2024)

  Upper extremity prostheses vary based on patients' articulation levels and movement methods. They can be cosmetic, operate mechanically with shoulder movement, or be controlled by myoelectronic and electroencephalography ...

• 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 ...

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