Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Assessment of the Quality of Tuffs in Central Anatolia, Turkey: A Quantitative Classification Approach(Acad Sci Czech Republic Inst Rock Structure & Mechanics, 2025-12-03) Koken, Ekin; Ince, IsmailThe growing global demand for dimension stones necessitates efficient and accurate evaluation methods to ensure their optimal use in various industries. To assess their suitability for various dimension stone applications, this study investigates tuffs from Central Anatolia, Turkey. For this purpose, the fundamental physical and mechanical properties of the tuffs were determined in laboratory studies, and a detailed durability assessment was conducted for each rock type. The analysis results indicate that most of the examined rocks are of low quality and more suitable for non-load-bearing applications. Based on the collected data, fuzzy clustering techniques were applied to develop a new classification system, categorising the tuffs into four classes (Class A-D) according to their potential applications. Additionally, a user-friendly MATLAB-based software tool was also developed to facilitate the implementation of the proposed classification system.Conference Object Clean Energy Production and Decarbonization of Energy Sector With Floating Photovoltaic Systems(Institute of Physics, 2025-11-01) Bajc, T.; Ozgun, F.; Koca, K.; Karipoğlu, F.Floating photovoltaic systems (FPVS) offer several advantages over traditional land-based PV systems, which has contributed to a growing global interest in their deployment. Since the energy yields are strongly dependent on location and tilt angle of FPVS, this research focuses on the clean energy production and decarbonization potential of FPVS in Serbia and Türkiye for different water bodies, such are natural and artificial lakes and dams. The research is performed for the most appropriate lakes and dams, having in mind importance of the location, energy yields potential, distance from the electricity grid and main roads, environmental impact, water depth and land type quality. Tilt angles are analyzed in a range from 5 to 40°, and the optimal angle is depicted for selected locations. The highest energy yields for Türkiye were obtained for 30° tilt angle, while for Serbia it was 36°. The results showed that possible clean energy production in both countries reaches 15345 kWh of energy in total, while the yearly carbon emissions reduction for all selected locations goes up to 10.76 tCO<inf>2</inf>/year in total. Since the legal framework for the application of FPVS is not established yet in observed countries, these results contribute to the future development of legislation in the field of FPVS and encourage the stakeholders to invest in clean energy production. © Published under licence by IOP Publishing Ltd.Conference Object Offshore Floating Modular Energy Islands: Technologies and Challenges(Institute of Physics, 2025-11-01) Gkantou, M.; Amlashi, H.; Snæbjörnsson, J.; Skejic, D.; Ferri, G.; Marino, E.; Baniotopoulos, C.Offshore floating modular energy islands (FMEIs) represent a promising solution to meet growing global energy demands, while addressing challenges associated with conventional energy infrastructure. This paper explores key technological components underpinning the design, construction, and energy generation of FMEIs, with a focus on three core areas: energy generation systems, floating structures and construction methods. The first technological component focuses on energy generation systems, examining the technologies of offshore wind power, solar and wave energy, to maximise overall energy production, while also highlighting the challenges involved in integrating these technologies. The second section examines the support structure of offshore floating platforms, as well as the key role of mooring systems in ensuring structural integrity under challenging marine conditions. The importance of advanced monitoring and maintenance strategies for long-term viability is also discussed. The third technological component discusses modular construction, highlighting the material choices and associated construction challenges in building FMEIs. This review also includes case studies and ongoing projects that demonstrate the real-world application of these technologies. Through the integration of advanced renewable energy generation technologies, floating and mooring systems and modular construction methods, FMEIs offer a sustainable and innovative approach to offshore energy production. This paper provides an overview of FMEIs and contributes to advancing development in this emerging field. © Published under licence by IOP Publishing Ltd.Conference Object Modular Floating Energy Islands With Green Hydrogen Integration: Design of a Small-Scale P2x Scheme(Institute of Physics, 2025-11-01) Akpolat, A.N.; Cundeva, S.; Todorovic, J.; Rexhepi, V.; Okhay, O.; Bakon, T.; Borg, R.P.The climate crisis and rising carbon emissions make the integration of renewable energy systems into electricity grids worldwide inevitable. In this context, modular floating energy islands (MFEI) provide innovative solutions for hybrid systems with high renewable energy penetration. This study explores the simultaneous use of various renewable resources, such as solar, wind, tidal, and wave energy, through small-scale MFEI structures that can be situated in seas and lakes. Thanks to their modular design, these systems offer benefits like scalability, portability, and ease of maintenance, allowing for flexible and adaptive developments in the energy infrastructure. As highlighted in recent literature (e.g., the North Sea Wind Power Hub and EU H2Ocean projects), offshore structures for green hydrogen production support energy storage and carbon-free fuel conversion within the Power-to-X (P2X) framework. This study evaluates the potential of photovoltaic (PV)-supported hydrogen production in MFEI structures through numerical analyses. The results emphasize the strategic role of these structures in enhancing energy security, coastal protection, and reducing carbon emissions by producing significant amounts of hydrogen. This hydrogen can be used for various purposes, including re-electrification, industrial applications, heating, and agriculture. Future research should focus on real-time data optimization, AI-supported system management, and integrated hydrogen consumption scenarios. © Published under licence by IOP Publishing Ltd.Article Toward the Design of New Α-Carboline Derivatives Against Anaplastic Lymphoma Kinase (Alk): A Comprehensive in Silico Approach(Wiley-VCH Verlag GmbH, 2025-11) Sari, Ceyhun; Akcok, IsmailAfter the first description of anaplastic lymphoma kinase (ALK) in an anaplastic large cell lymphoma cell line as a nucleophosmin (NPM) fusion partner, ALK and its various fusion partners have been implicated in numerous cancers such as non-small cell lung cancer (NSCLC), anaplastic large cell lymphoma (ALCL), neuroblastoma, and rhabdomyosarcoma. In the last decade, several compounds targeting ALK have been developed and approved by the Food and Drug Administration (FDA). Despite the advances of generations of ALK inhibitors, a recent study highlighted that around half of the ALK-positive NSCLC patients will go through disease progression in response to first-line alectinib, which is a second-generation ALK inhibitor. In this study, we aimed to propose a novel alpha-carboline compound targeting the ALK tyrosine kinase domain to be used against various types of cancer in which ALK fusion proteins may be involved. In this regard, we designed more than 200 alpha-carboline derivatives and investigated their binding properties against ALK tyrosine kinase by using in silico protocols consisting of molecular docking studies, molecular dynamics simulations, MM/PBSA binding free energy calculation, and essential dynamics analysis. Considering the obtained results, we developed two promising candidates, compounds 208 & 209 with -9.05 and -9.80 binding energies, respectively, which demonstrated improved binding profiles over the course of a 300 ns simulation.Article Boundaries of Belonging: the Spatial and Social Logic of Being Yilli People in Kayseri(Sage Publications Inc, 2025-11-26) Mus Ozmen, Nihan; Asiliskender, Burak; Ozmen, ZehniThis study explores the spatial, social, and cultural dynamics of being yilli, a deeply rooted local identity in Kayseri, Turkey. Drawing on ethnographic fieldwork, oral histories, and spatial analysis, it examines how the yilli people negotiate urban transformation through selective adaptations to modernization while maintaining traditional social boundaries. The research shows that the yilli do not passively resist change but actively reinterpret modernization to reinforce status, kinship, and symbolic belonging. Spatial relocation and investment patterns reflect economic strategies and efforts to preserve cultural distinction amid urban expansion. The findings demonstrate that urban transformation in Kayseri is both a material and cultural process, shaped by layered histories of memory, hierarchy, and social imagination. Through the case of the yilli, the study contributes to broader debates in urban sociology and cultural geography, offering insights into how culture-centered societies adapt to and reshape modernization processes.Article Forecasting the Consumer Price Index in Türkiye Using Machine Learning Models: A Comparative Analysis(Gazi Univ, 2025-09-01) Söylemez, İsmet; Ünlü, Ramazan; Nalici, Mehmet ErenThis study utilizes machine learning models to forecast Türkiye's Consumer Price Index (CPI), thereby addressing a critical gap in inflation prediction methodologies. The central research problem involves the forecasting of CPI in a volatile economic environment, which is essential for informed policymaking. The primary objective of this study is to evaluate the performance of three machine learning models, such as Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM), in forecasting CPI over periods ranging from one to six months, utilizing data from 2012 to 2024. The study's unique contribution lies in the application of the \"SelectKBest\" method, which identifies the most relevant indices, thereby enhancing the efficiency of the models. An ensemble method, Averaging Voting, is also employed to combine the strengths of these models, producing more accurate and robust predictions. The findings indicate that while the RF model consistently generates the most accurate forecasts across all shifts, the SVM model demonstrates a particular strength in the domain of short-term predictions. The ensemble model demonstrates a substantial performance improvement, with a R2 value of 0.962 for one-month ahead of estimates and 0.956 for five-month forecasts. This combined approach has been shown to outperform individual models, offering a more reliable framework for CPI forecasting. The findings offer valuable insights for economic policymakers, enabling more precise and stable inflation predictions in Türkiye.Article Citation - WoS: 7Citation - Scopus: 4Separation of Fe and Mn From Manganiferous Iron Ores via Reductive Acid Leaching Followed by Magnetic Separation(Springer, 2019-08-01) Top, S.In this study, a process to separate manganese and iron from manganiferous iron ores by reductive acid leaching followed by magnetic separation was conceived and experimentally tested. In the leaching process, sulfuric acid was used as lixiviant and oxalic acid was used as reductant. The experimental results showed that the manganese and iron separation was optimum when the concentration of the sulfuric acid and oxalic acid were 0.75 M and 30 g/L, respectively, at a temperature of 80 °C, a solid/liquid ratio of 67 g/L, stirring speed of 400 rpm, and leaching duration of 60 min. Under this condition, 90.49% and 6.78% of Mn and Fe were dissolved, respectively, from the ore sample with a size fraction of − 106 μm. It was determined that the leaching of manganese from the ores was a second-order reaction with an activation energy (E<inf>a</inf>) of 53.38 kJ/mol. The leaching residues obtained under the optimum condition were subjected to high-intensity wet magnetic separation tests to recover the remaining iron content. This separation process produced a concentrate containing 56.20% Fe and 1.79% Mn with iron and manganese recoveries of 56.83% and 66.73%, respectively. A magnetic separation test from an unleached ore sample was also carried out as a benchmark. To the best of our knowledge, this is the first time that a magnetic separation process was used to a residue obtained from reductive acid leaching of manganiferous iron ores to recover iron. © 2019, Society for Mining, Metallurgy & Exploration Inc.Conference Object Cyber Threats to Green Hydrogen Production Within a Solar Microgrid(Springer International Publishing AG, 2025) Bozdal, Mehmet; Pourmirza, ZoyaThe transition towards sustainable energy systems depends heavily on the reliable operation of renewable energy infrastructure, which is increasingly interconnected and digitized. Therefore, ensuring cybersecurity resilience is essential for maintaining the reliability and safety of renewable energy systems in a rapidly evolving digital landscape. This paper investigates the economic implications of data integrity and system configuration attacks on a green hydrogen production system within a solar microgrid. Through a comprehensive analysis, the vulnerability of the system to cyber intrusions that manipulate relay settings, electricity prices, and hydrogen level, is examined. Drawing on a multidisciplinary framework encompassing energy economics, cybersecurity, and renewable energy technologies, a methodological approach is developed to quantify the direct economic impacts of attacks. Simulation results indicate that such attacks can decrease profits by up to 14%.