Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
Browse
20 results
Search Results
Now showing 1 - 10 of 20
Article A Phenomenological Kinetic Flotation Model: Intrinsic Floatability Profiling for Batch and Continuous Flotation Systems(Springer Heidelberg, 2026) Polat, Mehmet; Guzel, Veli; Kobas, Muammer; Polat, HurriyetThis study presents a mechanistic flotation kinetics model that unifies the description of mineral particle floatability in both batch and continuous systems. Building on a physically explicit interpretation of bubble-particle interactions, the model introduces the concept of intrinsic floatability, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\upphi }_{\text{P},\text{ij}}<^>{\text{s}}$$\end{document}, defined as the size-and composition-dependent probability that a particle within a bubble's sweep volume reports to the froth. A central feature of the framework is that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\upphi }_{\text{P},\text{ij}}<^>{\text{s}}$$\end{document} is decoupled from system-level rate-determining factors, such as bubble-particle encounter frequency, transport limits, and bubble surface crowding-that otherwise confound attempts to extract floatability distributions from kinetic data. This separation is achieved through three explicit, time-dependent parameters: the encounter rate kappa(t), the limiting flotation rate mu(t), and the bubble saturation factor chi(t). Together, these parameters isolate intrinsic particle behavior from external constraints. The model naturally reduces to the classical first-order rate law in dilute pulps, while in concentrated suspensions it predicts systematic deviations, approaching zero-order kinetics as bubble surfaces saturate. Importantly, the same formulation applies seamlessly to batch tests and multi-stage continuous circuits, enabling a consistent theoretical framework across scales and ore types. Requiring only standard flotation data and known system parameters, the model is practical for both laboratory coal flotation studies and industrial non-coal applications. Validation using batch coal data and continuous plant-scale copper flotation results demonstrates its robustness and broad relevance.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 Citation - WoS: 2Citation - Scopus: 1Cross-Linked Carboxymethyl Cellulose Biosorbent for Zinc Removal: a Sustainable Remediation of Heavy Metal-Polluted Waters(Springer Heidelberg, 2025) Celgan, Dilber; Karadag, Asiye; Karim, Barna Jalaluddin Mohammad; Recepoglu, Yasar Kemal; Arar, OzgurThis study focuses on the preparation and characterization of cross-linked carboxymethyl cellulose (CMC) biosorbent for efficient removal of Zn2(+) ions from aqueous solutions. The microstructural features of the biosorbent were examined using scanning electron microscopy (SEM), while elemental analysis was conducted using an elemental analyzer to determine carbon (C), hydrogen (H), nitrogen (N), and sulfur (S) content. Fourier transform infrared (FTIR) spectroscopy was employed to identify functional groups within the biosorbent. Sorption experiments revealed that increasing the biosorbent dose led to higher Zn2(+) removal rates until equilibrium was reached. The optimal pH for Zn2(+) removal was determined to be >= 5, attributed to the conversion of acetate group to its ionic form. Rapid kinetics were observed, with 99% removal achieved within 5 min. The biosorbent exhibited a maximum sorption capacity of 10.809 mg/g and a removal rate of 99% at pH 5. Desorption studies demonstrated efficient Zn2(+) recovery using 0.25 M HCl solution, with a total desorption rate exceeding 99%. The findings indicate the potential for cost-effective regeneration of the biosorbent using dilute acid solutions, enhancing its sustainability and practical applicability in water purification processes. Additionally, the biosorbent's selectivity for Zn2(+) ions over competing ions and its effectiveness in treating real water samples, including those containing Na+, K+, Ca2(+), and Mg2(+), highlight its suitability for practical water purification applications.Article Citation - WoS: 1Citation - Scopus: 1Tracing the Origins: Byzantine Lime Mortars From Anaia and St. Jean Churches (Western Türkiye) and Provenances of Natural Stone Aggregates(Springer Heidelberg, 2025) Aydinalp, Tugce; Uzelli, Taygun; Sagin, Elif UgurluThe aim of this study is to determine the provenances of natural stone aggregates of the lime mortars from the St. Jean and Anaia Churches, which represent two of the most significant Byzantine buildings in Western T & uuml;rkiye. With this aim, the characterization study was conducted to define the physical properties and raw material compositions of lime mortars; hydraulic properties of the binders; mineralogical and chemical compositions, microstructural properties of lime, binders and aggregates; geochemical characteristics and pozzolanic activities of aggregates. The analyses were determined using X-ray diffraction (XRD), scanning electron microscopy coupled with energy dispersive spectroscopy (SEM-EDS), and thermogravimetric analysis (TGA). Furthermore, field observations and analytical studies were paired with the characterization results to determine the possible provenances. Analytical studies demonstrated that natural stone aggregates exhibited highly pozzolanic properties, which imparted hydraulicity to lime mortars. The macrostructure of the natural stone aggregates exhibited angular characteristics and a diverse lithological composition derived from the older brecciated clastics of the Menderes Massif. The fine-grained volcanic matrix of the aggregates was predominantly dacitic or rhyolitic in character, possibly derived from a breccia matrix composed of volcaniclastic materials. The findings suggested that the provenance of the natural stone aggregates were the breccia accumulation regions around Ayasuluk (Sel & ccedil;uk) for the St. Jean Church and S & ouml;ke-Germencik for the Anaia Church. The deliberate selection of natural stone sources to produce hydraulic lime mortars shows a conscious relationship with the surrounding geology during the Byzantine period.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.