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Investigation of the Effects of Statistically Significant Features on the Classification of EEG-Based Motor Imagery Tasks

Murside Degirmenci

Motor imagery (MI) task classification is highly prevalent in Electroencephalography (EEG)-based Brain-Computer Interface (BCI) research area. Extremity movement task classification and finger movement classification studies are presented in this thesis. In extremity movement classification, binary-class (right hand and left hand) and multi-class (right hand, left hand, right hand, and left hand) classifications are performed using 4 different feature extraction approaches and statistically significance-based feature selection (the independent t-test, one-way ANOVA test). Firstly, time- ...Daha fazlası

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Manufacturing Duplex Steel by Using Induction Furnaces and Characterization

Gülşah Uslu

Duplex steels are materials that contain ferrite and austenite phases in their structure, have high resistance to corrosion, and also show improved mechanical values. While the austenite in its structure provides general corrosion resistance and ductility, ferrite provides resistance to stress corrosion cracking and mechanical strength. Duplex steels have widespread use, especially in shipping and petrochemistry. The current production method of duplex steels, which are in demand with a wide usage area, is generally argon oxygen decarburization furnaces (AOD). In addition to the production met ...Daha fazlası

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Performance Study of Darrieus Turbine Using Numerical Simulation

Abdelrahman ABUALEENEIN

In this study, CFD abilities to handle Darrieus turbine simulation were assessed and validated in light of related experimental and numerical studies. Simulation methodology is based on two-dimensional modeling of a double NACA 0018 bladed, straight blade Darrieus turbine. Modeling approach, meshing procedure, and solution parameters are mentioned and discussed in details. ANSYS fluent 18.2 is used to carry out all simulations. Experimental test’s data from literature [11] are implemented in context of results verification, also, Courant number and y plus analyses were provided. Due to the sim ...Daha fazlası

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Automated Captioning of Image and Audio for Visually and Hearing Impaired

Özkan Çaylı

Generating captions and text descriptions of images will enable visually and hearing impaired extended accessibility to the real-world, thus reducing their social isolation, and improving their well-being, employability, and education experience. This thesis presents significant advancements in algorithmic approaches for generating captions and text descriptions. These enhancements are pivotal in processing and interpreting both image and audio data. The focus on algorithmic innovation ensures that the platform is not only efficient but also adaptable to various types of visual and auditory in ...Daha fazlası

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Software Engineering Department Master Thesis

Mamadou Lamarana Diallo

Son zamanlarda yapay zeka (AI), sunduğu çözümler nedeniyle bilimsel araştırmaların tüm alanlarını işgal etti. Sağlık da bir istisna değil. Diyabet dünyadaki en yaygın hastalıklardan biridir. Komplikasyonlarından biri, hastanın görüşünü bulanıklaştırabilen veya bozabilen ve körlüğün ana nedenlerinden biri olan diyabetik retinopatidir. Diyabetik retinopatinin erken teşhisi tedaviye büyük ölçüde yardımcı olabilir. Yapay Zeka ve özellikle derin öğrenme alanındaki son gelişmeler, birçok hastalığı erken evrelerinde tahmin etmek, öngörmek ve teşhis etmek için kullanılabilecek iddialı çözümler sunmakt ...Daha fazlası

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Natural Language Processing and Machine Learning-Based Medical Decision Support Application Concept Design for Gastroesophageal Reflux Disease

Tevfik Aşgın

This text discusses a project for a concept design that aims to help doctors better diagnose and treat Gastroesophageal Reflux Disease (GERD) using the latest methods in artificial intelligence (AI), specifically LangChain and ChatGPT-4 from OpenAI. The project includes creating a system for GERD, using AI to work with medical data, testing the system with some patient cases, and seeing how well it helps in treating GERD. The project seeks to explore the feasibility of implementing a system that enhances the diagnosis and treatment through the application. 50 cases were generated for evaluatio ...Daha fazlası

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Electrochemical Detection of Dopamine Using a Simple Redox Cycling-Based Device

İpek AVCI

In order to understand brain function, diagnose disorders and develop precise treatments, the detection of dopamine using electrochemical devices is important. The detection of dopamine using electrochemical devices continues to be investigated, as evidenced by studies in the literature in recent years. This is because it helps to unravel the complexity of brain function, facilitate the diagnosis of neurological disorders and enable the development of precise treatments. These devices are important in neuroscience and medicine.

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Design and Development of a Multi Degree of Freedom Surgical Robot Manipulator that will be Utilized in Single Incision Laparoscopic Surgery

Mustafa Volkan YAZICI

This thesis focuses on design and development of a robot manipulator with dexterous forceps for single-incision laparoscopic surgery. Integrating the robotic capabilities into laparoscopy instruments, the study aims to increase precision and reduce limitations such as mobility constraints. Main objective of the thesis is to develop a robotic articulating laparoscopy instrument. In light of the first trials, it is seen that the dexterity and robotic control advantages are promising while the trocar's mobility constraint limits the workspace of the robotic laparoscopy forceps. An alternative sur ...Daha fazlası

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Ischemic Stroke Lesion Segmentationin MRI Images Using U-ShapedConvolutional Neural Network

Ilayda Alpay

İnme, günümüzde dünyada önde gelen ölüm nedenlerinden biridir. İnme geçiren hastaların tedavisi ve hayatta kalması için acil ve kesin tanı çok önemlidir. İskemik inmenin tanı ve tedavisi çoğunlukla manyetik rezonans görüntülemeye (MR) dayanmaktadır. Bu çalışmanın amacı, 2 boyutlu MR görüntüleri kullanarak U şeklinde bir evrişimsel sinir ağı mimarisi (CNN) oluşturarak iskemik inme lezyonunu bölütlemek ve çeşitli kayıp fonksiyonları kullanarak çalışmanın kayıp sonuçlarını, zar benzerlik katsayısını (DSC), hassasiyetini ve özgünlüğünü değerlendirmektir. Oluşturulan modeli eğitmek, doğrulamak ve t ...Daha fazlası

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Artificial Intelligence Based Resource Allocation in Cell-Free Networks

Mert Demirel

With the rapid development of technology, cellular networks can no longer meet the demands of wireless networks. Communication systems need to be updated to ensure that every user equipment (UE) receives accurate and efficient service. Cell-free (CF) networks offer advantages over cellular networks, such as more flexible resource allocation, higher capacity, better coverage and lower interference. The deployment of multiple access points (APs) and flexible allocation of resources leads to higher network performance and efficiency. In addition, in CF networks, users can communicate with ...Daha fazlası

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Improvement of engineering properties and liquefaction reduction of sandy soils using electric arc furnace slag and roof tile powder

Agolli, Drinela

The scarcity of suitable land for construction of engineering facilities and shortage of natural earth aggregates has highlighted the need for finding innovative way of construction. Nowadays problematic soils such as: soft clay, organic soils and liquefiable soils can be improved to the required civil engineering requirements by application of soil stabilization. Soil stabilization is a method intended to increase or preserve the stability of soil mass and chemical alteration of soil to improve engineering properties. Generally, ground treatment techniques used are: densification, reinforcem ...Daha fazlası

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Heart Attack Analysis Detection System Using Machine Learning Methods

SERDAR YANIK

In order to investigate Heart Attack Analysis and Detection Using Machine Learning Methods, models that predict the type of news in a new condition determined by using Machine Learning Models have been studied. In particular, the performance of various classifiers, including logistic regression, Knearest neighbour (KNN), support vector machine (SVM), Naive Bayes and decision tree, is compared. In the experiments using a real-life dataset, logistic regression and SVM gave the best results with a test accuracy of 90%. Naive Bayes achieved an accuracy of 86.67%, KNN 83.33% and decision tree 63.33 ...Daha fazlası

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