• Gözlemsel Kozmoloji ve Karanlık Madde Özetkileşimleri 

  Çamlıbel, Ali Kazım (2019)

  24 Şubat 2024’de ansızın aramızdan ayrılmasıyla hepimizi derinden üzen Prof. Dr. Durmuş Ali Demir, Yüksek Enerji Fiziği alanında çalışan ve bu alana yaptığı katkılarıyla uluslararası düzeyde tanınan bir fizikçiydi. ...

• Pantheon update on a model-independent analysis of cosmological supernova data 

  Çamlıbel, Ali Kazım; Semiz, İbrahim; Feyizoǧlu, M. Akif (IOP Publishing, 2020)

  We present an update of our previous work, necessitated by availability of a significantly improved dataset. The work is a model-independent analysis of the cosmological supernova (type Ia) data, where function families ...

• From Quantum Mechanics, Classical Mechanics and Bioinformatics to Artificial Intelligence Studies in Neurodegenerative Diseases 

  Habiboğlu, Mehmet Gökhan (2021)

  This volume provides computational methods and reviews various aspects of computational studies of protein aggregation. Chapters discuss the relationship between protein misfolding and protein aggregation, methods of ...

• Glycopeptides by quantum chemistry and artificial intelligence 

  Habiboğlu, Mehmet Gökhan (2018)

  Glycation destroys or impairs the biological function of peptides and proteins. The bacteria cell wall polymers consist of GlcNAc, which is crosslinked with oligopeptides. While glutamine is a nonessential amino acid ...

• Katkı malzemelerinin polimerik yalıtkanların manyetik geçirgenliğine etkisinin incelenmesi 

  Nişancı, Salih (2020-2021)

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• A Machine Learning Approach to Predict the Sepsis Status: Analyzing the Connection Between Relevant Laboratory Values and Other Physiological Measurements Obtained in Intensive Care Unit 

  Moghaddamnia, Sanam; Bozkurt, Mehmet Recep (2021)

  Sepsis is a life-threatening disease caused by the body's response to an infection, which leads to tissue damage, organ failure and death. According to literature, about 1.7 million Americans each year suffer from sepsis ...

• On the efficiency of LSTM in classifying musical impressions from EEG recordings 

  Kaya, Burak; Habiboğlu, Mehmet Gökhan; Moghaddamnia, Sanam (2023)

  The objective of this study is the classification of musical impressions with long short-term memory (LSTM) approach using EEG recordings of 20 subjects, while listening to different music genres. For this purpose, a deep ...

• Parameter and feature selection in decision trees for the classification of musical impressions from EEG records 

  Ozaltun, Emir Atakan; Moghaddamnia, Sanam; Habiboğlu, Mehmet Gökhan (2023)

  Reliable classification of different emotions is an important issue for emotional interaction between humans and computers. Therefore, this study aims at assessing the performance of decision trees in classifying musical ...

• Hybrid Tokenization Strategy for Turkish Abstractive Text Summarization 

  Kayalı, Nİhal Zuhal (2024)

  Text summarization is a significant topic in natural language processing. Tokenization approaches are important in this regard as they underpin text recognition and processing. The aim of this paper is to research the ...

• Konvolüsyonel sinir ağları (CNN) ile Çin sayı orüntülerinin sınıflandırması 

  Kayalı, Nİhal Zuhal; Omurca, Sevinç İlhan (2021)

  The MNIST dataset, which has become a standard for Machine Learning and Deep Learning applications, is quite popular. In thisstudy, a dataset containing images of handwritten Chinese numbers is introduced as a variation ...

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