• Performance and security of AES, DES, and RSA in hybrid systems: An empirical analysis of triple encryption 

  Özer, Erman; Aydos, Hasan (2024)

  This study evaluates the performance and security of three cryptographic algorithms— AES, DES, and RSA—individually and in hybrid combinations. It aims to enhance information security through a novel three-step hybrid ...

• Classification and analysis of agaricus bisporus diseases with pre-trained deep learning models 

  Albayrak, Ümit; Gölcük, Adem; Aktaş, Sinan; Coruh, Uğur; Taşdemir, Şakir; Baykan, Ömer Kaan (MDPI, 2025)

  This research evaluates 20 advanced convolutional neural network (CNN) architectures for classifying mushroom diseases in Agaricus bisporus, utilizing a custom dataset of 3195 images (2464 infected and 731 healthy mushrooms) ...

• Stochastic gompertzian model for parathyroid tumor growth 

  Partal, Tuğçem; Bayram, Mustafa (Wiley, 2025)

  In this paper, we study on the behavior and growth of parathyroid tumor in the human body. We investigate the change of parathyroid cancer cell with respect to time, obtained from the deterministic Gompertz model through ...

• The SVM-ARIMA fusion approach for forecasting the structural integrity of obsidian substitution mortars 

  Çakmak, Talip; Yılmaz, Yıldıran; Ustabaş, İlker (IEEE, 2024)

  The construction materials used in building design have changed over time, and their properties continue to evolve. Concrete possesses important characteristics such as high strength, durability, low cost, and easy ...

• A new objective diagnostic tool for attention-deficit hyper-activity disorder (ADHD): development of the distractor-embedded auditory continuous performance test 

  Özaslan, Ahmet; Sevri, Mehmet; İşeri, Elvan; Karacan, Barış; Cengiz, Mehmet; Karacan, Hacer; Sarıpınar, Esin Gökçe; Dikmen, Asiye Uğraş; Güney, Esra (MDPI, 2024)

  Background/Objectives: Attention-Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity. Traditional diagnostic methods, which depend ...

• Utilizing hybrid encryption methods to ensure the security of financial transactions 

  Özer, Erman; Aydos, Hasan (IEEE, 2024)

  This study aims to examine and evaluate encryption techniques used to enhance the security of financial transactions in banking systems. The focus is on fundamental encryption algorithms such as AES (Advanced Encryption ...

• Social media use and negative emotions: a survey of university students 

  Dennen, Vanessa P.; Yalçın, Yasin (IADIS, 2024)

  This study examines how university students experience negative emotions due to social media use and also provides initial validation of the Social Media Negative Emotion Questionnaire. Findings show that the degree to ...

• Design and optimisations of metal-oxide artificial synaptic device based machine learning model 

  Yılmaz, Yıldıran; Gül, Fatih (IEEE, 2024)

  Synaptic device-based neural network models are increasingly favored for their energy-efficient computing capabilities. However, as the demand for scalable and resource-efficient computing solutions continues to grow, there ...

• Comparative analysis of computational intelligence techniques in financial forecasting: A case study on ANN and ANFIS models 

  Özer, Erman; Sevinçkan, Nurullah; Demiroğlu, Erdem (Institute of Electrical and Electronics Engineers Inc., 2024)

  This paper explores the evolution of financial analysis and forecasting models, contrasting traditional statistical methods with computational intelligence techniques. While conventional methods like autoregressive moving ...

• Neuro-inspired hardware solutions for high-performance computing: A TiO2-based nano-synaptic device approach with backpropagation 

  Yılmaz, Yıldıran; Gül, Fatih (Elsevier, 2024)

  Computer-based machine learning algorithms that produce impressive performance results are computationally demanding and thus subject to high energy consumption during training and testing. Therefore, compact neuro-inspired ...

• Predicting mechanical properties in geopolymer mortars, including novel precursor combinations, through XGBoost method 

  Yılmaz, Yıldıran; Çakmak, Talip; Kurt, Zafer; Ustabaş, İlker (Springer, 2024)

  Concrete is the most widely used material in the building industry due to its affordability, durability, and strength. However, considering carbon emissions, it is believed that concrete will be replaced by geopolymers in ...

• Increasing the performance of a hospital department with budget allocation model and machine learning assisted by simulation 

  Alim, Muzaffer; Yılmaz, Yıldıran; Boz, Esra (Taylor & Francis Inc., 2024)

  The COVID-19 pandemic highlighted the critical need for efficient resource management in healthcare. In this study, the internal medicine outpatient clinic in a hospital is modelled by simulation method. Appropriate ...

• Recurrent neural network and long short-term memory models for audio copy-move forgery detection: a comprehensive study 

  Akdeniz, Fulya; Becerikli, Yaşar (Springer, 2024)

  One of the most pressing challenges in audio forgery detection—a major topic of signal analysis and digital forensics research—is detecting copy-move forgery in audio data. Because audio data are used in numerous sectors, ...

• Stacked ensemble modeling for improved tuberculosis treatment outcome prediction in pediatric cases 

  Yılmaz, Yıldıran (Wiley, 2024)

  The promising results of ML (machine learning) methods in various disciplines have led to the frequent use of these methods in health fields such as disease diagnosis, personalized medicine, medical image-based diagnosis, ...

• Machine learning based feature optimization and early detection system in heart diseases 

  Özer, Erman; Aydos, Hasan (IEEE, 2023)

  In today's world, humanity faces a myriad of challenges, many of which pose significant threats to our well-being. Chief among these challenges are health-related issues. Among these health problems, heart diseases stand ...

• ANOVA method reveals key factors influencing geopolymer strength: A comprehensive evaluation of input variables 

  Yılmaz, Yıldıran; Çakmak, Talip; Kurt, Zafer (IEEE, 2023)

  In this study, we present an ANOVA (Analysis of Variance) method conducted on a geopolymer dataset. The analysis focuses on evaluating the impact of various input variables, including OB, GW, FA, S, M, M/B, AGE, HEAT, SiO2, ...

• Learner characteristics and competencies 

  Yalçın, Yasin (Springer, 2023)

  The advances in technology and the demand for open, distance, and digital education redefined the characteristics and competencies of learners in these learning environments. Although technology ownership and access to an ...

• Accuracy improvement in Ag:a-Si memristive synaptic device-based neural network through Adadelta learning method on handwritten-digit recognition 

  Yılmaz, Yıldıran (Springer, 2023)

  Traditional computing architecture (Von Neumann) that requires data transfer between the off-chip memory and processor consumes a large amount of energy when running machine learning (ML) models. Memristive synaptic devices ...

• A novel framework for strength prediction of geopolymer mortar: Renovative precursor effect 

  Kurt, Zafer; Yılmaz, Yıldıran; Çakmak, Talip; Ustabaş, İlker (Elsevier, 2023)

  Concrete is the most used building material today as it has many advantages due to its structure. Geopolymer composites could potentially replace concrete in the future due to the demands of the construction industry. The ...

• An investigation of the factors that influence online learners' satisfaction with the learning experience 

  Yalçın, Yasin; Dennen, Vanessa P. (Springer, 2023)

  Online learning environments offer flexibility for learners who would like to study at a distance. However, research informs us that online learners are usually less likely to complete the learning experience and more ...

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