Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Damage Assessment of Structures Following the February 6, 2023 Kahramanmaraş Earthquakes: A Dataset-Based Case Study in Gaziantep, Türkiye(Springer Heidelberg, 2025) Atasever, Kurtulus; Aydogdu, Hasan Huseyin; Narlitepe, Furkan; Goksu, Caglar; Demir, Ugur; Demir, Cem; Ilki, AlperFollowing the 2023 Kahramanmara & scedil; Earthquakes (Mw 7.7 and 7.6) that struck T & uuml;rkiye on February 6, 2023, the Ministry of Environment, Urbanization, and Climate Change (MoEUCC) initiated a large-scale post-earthquake damage assessment campaign, targeting more than 2,3 million structures within the affected region. A comprehensive field survey was carried out in and around Gaziantep, one of the most severely affected cities. The authors assessed more than 1700 structures representing a wide range of occupancy types, including residential, educational, healthcare, religious, administrative, industrial, and lodging structures. In this paper, the methodological process of post-earthquake data collection in and around Gaziantep is presented, together with the data on the distribution of damage with respect to construction period, number of stories, and building occupancy type, to ensure a complete understanding of the extent and characteristics of structural damage. The damage assessment employed two data sources: (i) the data gathered through the authors' newly developed, novel damage-assessment software, presented here for the first time, and (ii) the official post-earthquake damage database of the MoEUCC. A further novelty of this study is the presentation of the largest dataset to date for the investigated earthquake doublet, encompassing approximately 1700 buildings. Additionally, the relationship between damage states, peak ground accelerations, and fault distances is thoroughly investigated. The detailed earthquake-hit site investigations revealed that the examined structures displayed structural inadequacies akin to those witnessed in previous seismic events, with a notable focus on the arrangement of the structural system, the quality of construction materials and reinforcement detailing.Article A Robust Possibilistic Semi-Supervised Fuzzy Clustering Algorithm With Neighborhood-Aware Feature Weighting(Springer Heidelberg, 2025) Moghaddam, Arezou Najafi; Aghazadeh, Nasser; Hashemzadeh, Mahdi; Oskouei, Amin GolzariThe Semi-Supervised Fuzzy C-Means (SSFCM) method integrates class distribution information with fuzzy logic to overcome the challenges of semi-supervised clustering methods. While the inclusion of label information in the objective function improves the quality of the clustering method, semi-supervised fuzzy techniques still encounter important limitations, including (1) sensitivity to noise and outliers, (2) uniform feature importance, (3) neglecting the influences of neighborhood in the clustering process. In this paper, an improved semi-supervised clustering algorithm is presented to address these challenges. First, the algorithm reduces the sensitivity to noise and outliers by integrating the possibilistic fuzzy C-means algorithm into the SSFCM method. Second, a dynamic feature weighting method assigns different weights to the features in each cluster, which improves the performance of the algorithm in imbalanced datasets. Third, the proposed algorithm introduces a neighborhood mechanism that incorporates the neighbor's trade-off weighting and feature weighting strategy considering a strong metric. Finally, a robust kernel metric is used to further improve the performance on complex and nonlinear datasets. Extensive experiments are conducted on several benchmark datasets to evaluate the performance of the proposed method. The results show that the proposed method outperforms the current state-of-the-art techniques. The implementation source codes of the proposed method are publicly available at https://github.com/Amin-Golzari-Oskouei/RPSSFC-NAFW.Article Enhanced Wear Resistance of Epoxy Composites Through the Incorporation of Diatom Frustules: a Multi-Objective Optimization Approach(Springer Heidelberg, 2025) Gulturk, E.; Aydin, L.; Sahin, A. E.; Sinmazcelik, T.; Guden, M.The present work investigates the enhancement of wear resistance in epoxy composites through the incorporation of calcined and natural diatom frustules (CDFs and NDFs) as reinforcing fillers. The CDFs, pre-calcined at 1200 degrees C during manufacturing to improve structural integrity and eliminate organic matter, were supplied in processed form. Both CDFs and NDFs were subsequently wet-sieved (below 325 mesh) and dried at 120 degrees C for 2 h to ensure particle uniformity and moisture removal. Epoxy composites were prepared with 5-20 wt% frustule content. The fillers were ultrasonically dispersed in the epoxy matrix to improve uniformity and reduce agglomeration, followed by vacuum degassing and thermal curing. Wear performance was initially evaluated for all samples at a fixed 1000-cycle duration. Based on preliminary results, composites with 15 wt% and 20 wt% filler content which showed the highest wear resistance, were further tested under varying sliding distances corresponding to 300-1000 cycles to examine long-term behavior. Tests were conducted under dry sliding conditions using a block-on-ring tribometer at 50 N load. Using a systematic modeling-design-optimization framework, the study defines diatom weight fraction, sliding test duration, and frustule type as design variables. The experimental process was modeled through multiple nonlinear neuro-regression analyses, selecting the most realistic model based on Rtraining2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{{{\text{training}}}}<^>{2}$$\end{document}, Rtesting2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{{{\text{testing}}}}<^>{2}$$\end{document}, Radjusting2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_{{{\text{adjusting}}}}<^>{2}$$\end{document}, and stability evaluations from 13 functional structures, with a second-order trigonometric nonlinear type model (SOTN) as the highest predictive performance. Stochastic optimization methods-including Modified Differential Evolution (MDE), Modified Nelder-Mead (MNM), Modified Simulated Annealing (MSA), and Modified Random Search (MRS)-were employed under three design scenarios to determine optimal wear parameters. The results revealed that epoxy composites containing 15 wt% NDFs exhibited the most substantial improvement, with a 95% reduction in specific wear rate (SWR) compared to neat epoxy and a 60% reduction relative to CDF-filled composites. The lowest optimized specific wear rate achieved was 1.086 x 10-5 mm3/N<middle dot>m. This work offers a comprehensive framework integrating material processing, statistical modeling, and stochastic optimization for the design of high-performance, wear-resistant epoxy composites.Article Citation - WoS: 2Citation - Scopus: 2Experimental Integration of Stone Topologies To the Simplified Micro-Modeling for the Seismic Response of Masonry Walls: a Novel Insight(Springer Heidelberg, 2025) Demir, UgurThis study aims to explore the impact of stone typologies on the in-plane seismic behavior of stone masonry buildings. The present study aims to quantify the strength and deformability parameters such as lateral load capacity, ductility, energy dissipation capacity and stiffness degradation of frequently used sandstone and limestone masonry, which will intentionally contribute to the core body of knowledge on their original structural design, seismic safety evaluation and intervention design. The innovative aspect of this research lies in the holistic methodology that integrates field surveys to classify local stone masonry units, experimental characterization of the chemical and mechanical properties of these units to capture variability, and finite element modeling of the in-plane cyclic behavior of stone masonry walls using experimental data. A novel simplified micro-modeling approach is implemented within a standard finite element software, eliminating the need for user-defined subroutines. This approach significantly reduces computational efforts compared to conventional methods, making it particularly suitable for analyzing large-scale stone masonry structures. The study investigates the impact of chemical composition (sandstone or limestone), applied axial stress (0.25 MPa, 0.50 MPa, or 1 MPa), and wall aspect ratios (height-to-length ratios of 1.0 or 1.5) on wall performance. The modeling approach is validated against experimental results from the literature, demonstrating good agreement. Finally, the study assesses wall performance in terms of deformation limits in current seismic codes. The findings provide critical insights for developing innovative design strategies to enhance the structural integrity of stone masonry walls and improve the seismic assessment of existing structures.Article The Future of Urban Hierearchy and Zipf Law: Arima and Bats Forecasting(Springer Heidelberg, 2025) Duran, Hasan EnginZipf's Law is recognized as a power law which is used to identify the extent and the evolution of the urban hierarchies. The existing studies have mostly adopted a retrospective view by analysing the past patterns. However, we would like to shed a light onto the future trajectories. Therefore, the aim of this study is to investigate the future of Urban Hierarchies and Zipf's Law for the U.S. Metropolitan Statistical Areas (MSA) and the period 1969-2070. Having applied, two forecasting methods; i."ARIMA (Autoregressive Integrated Moving Average)", ii. "BATS (Exponential smoothing state space model Box-Cox transformation, ARMA errors, Trend and Seasonal components)" and the estimation of rank-size rule, we obtained crucial conclusions (Box and Jenkins in: Time series analysis: forecasting and control, Holden-Day, San Francisco, 1970; Box et al. in: Time series analysis: forecasting and control, Wiley, New Jersey, 2016; Kinney in Acc Rev 53:48-60, 1978; Hyndman et al. in R package version 8.24.0, https://cran.r-project.org/web/packages/forecast/forecast.pdf, 2025; De Livera in: Automatic forecasting with a modified exponential smoothing state space framework, Department of Econometrics & Business Statistics, Monash University (Working Papers 10/10). https://www.monash.edu/business/econometrics-and-business%20statistics/research/publications/ebs/wp10-10.pdf, 2010; De Livera et al. in: Forecasting time series with complex seasonal patterns using exponential smoothing. (Working paper 15/09), Department of Econometrics & Business Statistics, Monash University. https://robjhyndman.com/papers/ComplexSeasonality.pdf, 2010; De Livera et al. in J Am Stat Assoc 106:1513-1527, 2011). We provide evidence that the Zipf's Law is observed not to hold over the last century and, if existing conditions hold, it is not expected to be valid in the next 50 years. Pareto exponent is found significantly below the Pareto level, historically, currently and prospectively.Article Numerical Study of Breaching at Upper Parts of Homogenous Earthen Dams(Springer Heidelberg, 2025) Dumlu, Emre; Guney, Mehmet Sukru; Okan, Merve; Ozden, Guerkan; Tayfur, GokmenIn this study, time-dependent finite element analyses of the breaching process in two homogenous earth-fill dams were performed using the finite element method. Breaching was initiated at the middle and corner sections of the upper part of the dam bodies. The numerical results were compared with the findings of the experiments realized on dams 60 cm high, 2 m wide at bottom, 20 cm wide at crest with 1 V:1.5H side slopes at upstream and downstream faces. This numerical study combines time-dependent hydraulic gradient distributions and groundwater flows to assess breach areas, velocities, and flow rates. A Python algorithm was integrated with the Jupyter console, allowing the simulation of the breach mechanism in multiple runs to determine breach parameters. Both numerical and experimental analyses revealed that the dams were exposed to backward erosion, starting at the downstream side of the dam and progressing inward. The compatibility between experimental and numerical results was sought by means of the parameters RMSE, MAE and the statistical performance of the numerical approach was evaluated by using RSR, NSE, and PBIAS. A fairly good agreement was obtained between the experimental and numerical results.Article Citation - WoS: 4Citation - Scopus: 5Diffusion-Based Data Augmentation Methodology for Improved Performance in Ocular Disease Diagnosis Using Retinography Images(Springer Heidelberg, 2024) Aktas, Burak; Ates, Doga Deniz; Duzyel, Okan; Gumus, AbdurrahmanDeep learning models, integral components of contemporary technological landscapes, exhibit enhanced learning capabilities with larger datasets. Traditional data augmentation techniques, while effective in generating new data, have limitations, especially in fields like ocular disease diagnosis. In response, alternative augmentation approaches, including the utilization of generative AI, have emerged. In our study, we employed a diffusion-based model (Stable Diffusion) to synthesize data by faithfully recreating crucial vascular structures in the retina, vital for detecting eye diseases by using the Ocular Disease Intelligent Recognition dataset. Our goal was to augment retinography images for ocular disease diagnosis using diffusion-based models, optimizing the outputs of the fine-tuned Stable Diffusion model, and ensuring the generated data closely resembles real-world scenarios. This strategic approach resulted in improved performance in classification models and augmentation outperformed traditional methods, exhibiting high precision rates ranging from 85% to 76.2% and recall values of 86%, and 75% for 5 classes. Beyond performance enhancement, we demonstrated that the inclusion of synthetic data, coupled with data reduction using the t-SNE method, effectively addressed dataset imbalance. As a result of synthetic data addition, notable increases of 3.4% in the precision metric and 12.8% in the recall metric were observed in the 7-class case. Strategically synthesizing data addressed underrepresented classes, creating a balanced dataset for comprehensive model learning. Surpassing performance improvements, this approach underscores synthetic data's ability to overcome the limitations of traditional methods, particularly in sensitive medical domains like ocular disease diagnosis, ensuring accurate classification. The codes of the study will be shared on GitHub in a way that benefits everyone interested: https://github.com/miralab-ai/generative-data-augmentation.Article Citation - WoS: 1Citation - Scopus: 1Abnormally Accumulated Gm2 Ganglioside Contributes To Skeletal Deformity in Tay-Sachs Mice(Springer Heidelberg, 2024) Demir, Secil Akyildiz; Seyrantepe, VolkanTay-Sachs Disease is a rare lysosomal storage disorder caused by mutations in the HEXA gene, responsible for the degradation of ganglioside GM2. In addition to progressive neurodegeneration, Tay-Sachs patients display bone anomalies, including kyphosis. Tay-Sachs disease mouse model (Hexa-/-Neu3-/-) shows both neuropathological and clinical abnormalities of the infantile-onset disease phenotype. In this study, we investigated the effects of GM2 accumulation on bone remodeling activity. Here, we evaluated the bone phenotype of 5-month-old Hexa-/-Neu3-/- mice with age-matched control groups using gene expression analysis, bone plasma biomarker analysis, and micro-computed tomography. We demonstrated lower plasma alkaline phosphatase activity and calcium levels with increased tartrate-resistant acid phosphatase levels, indicating reduced bone remodeling activity in mice. Consistently, gene expression analysis confirmed osteoblast reduction and osteoclast induction in the femur of mice. Micro-computed tomography and analysis show reduced trabecular bone volume, mineral density, number, and thickness in Hexa-/-Neu3-/- mice. In conclusion, we demonstrated that abnormal GM2 ganglioside accumulation significantly triggers skeletal abnormality in Tay-Sachs mice. We suggest that further investigation of the molecular basis of bone structure anomalies is necessary to elucidate new therapeutic targets that prevent the progression of bone symptoms and improve the life standards of Tay-Sachs patients.Article Citation - WoS: 3Citation - Scopus: 2Development of Transition Metal Oxide Platforms for Aptasensing of Psa in Cell Cultures(Springer Heidelberg, 2024) Kirlangic, Irem Aydin; Uner, Goklem; Kara, Pinar; Kirmizibayrak, Petek Ballar; Ertas, Fatma NilIn this study, a novel aptasensor based on a transition metal oxide-modified pencil graphite electrode (PGE) was developed for the diagnosis of early-stage prostate cancer (PCa) via monitoring the prostate-specific antigen (PSA), which is the main biomarker for PCa. Single-use PGEs modified with pulsed deposited manganese oxide (MnOx) film were used to attach the amino-terminated aptamer specific to the PSA via carbodiimide chemistry. The designed aptasensor was placed in an electrochemical cell containing ferri/ferrocyanide ions as a redox probe to measure the charge transfer resistances (Rct) of the electrode surface by electrochemical impedance spectroscopy (EIS) to follow the response of each modification step. The effect of the medium pH on the ionic structure of the aptamer molecule according to its pI value and, thus, the reversing of the direction of the response (Delta Rct) by the pH change was also discussed. The level of PSA secreted from PCa cells was investigated using impedimetric transduction. The specificity of the aptasensor was validated through selectivity studies against non-specific tumor markers like VEGF and different cancer cell lines including breast cancer and androgen-insensitive prostate cancer. The developed system showcases a label-free, fast, specific, and cost-effective approach for PSA detection, highlighting the importance of medium pH and the electrostatic environment on the aptamer's response. Our work emphasizes the potential for such aptasensors in clinical diagnostics and paves the way for further exploration into using transition metal oxides in biosensing applications.Article A Methodology Providing New Insights Into the Flow Patterns of Karst Aquifers: an Example From Sw Türkiye(Springer Heidelberg, 2024) Maramathas, Athanasios; Katsanou, Konstantina; Sagir, Cagdas; Baba, Alper; Lambrakis, NikolaosThis paper presents a new and innovative methodology for the investigation of karst systems using spring discharge. The behaviour of springs in phase space is investigated by plotting the measurements of spring discharge versus the measurements of the water level at the spring's outlet. Such a diagram reveals new features of the function of the karst system and the discharge pattern of the spring that are not captured by common research methods. The application of this method to the Azmak Spring in southwestern T & uuml;rkiye revealed the existence of five distinct discharge subsystems that operate alternately and never simultaneously. They have a specific connection between them, while the transition from one to another is not random but follows a pattern. An attempt was made to interpret these features using concepts from percolation theory.