Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1926

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Preface
(IGI Global, 2025) Rousoulioti, T.; Pitsou, C.; Saglam, A.; Finch, K.
Through the Lens of the Documentary the Policy of Death in Prisons
(Turkish Medical Association, 2023) Özen Barkot, Z.
The prison is a space where the biopower most clearly prove itself. Prisons, as a mechanism that legitimizes and implements the standards of modern power on life processes, are places that determine “disposable lives” politically, socially, and culturally and make individuals open to death, by containing the disciplinary and coercive techniques that subjugate bodies. Thus, prisons are the most obvious manifestations of the power that authorizes itself over life and death and defines itself concerning the biological field under its control, potentially working together with necropolitics. Moreover, this process is constructed not only by the physical or concrete operation of power but also by narratives that give form and content to the sovereign. At this point, this article deals with the possibility of documentary films have an important function on truth and justice from a human rights perspective by deciphering the sovereign’s narrative. Specifically, the question of how necropolitics organizes itself in prison will be discussed in the scope of Errol Morris’s film entitled Standard Operating Procedure (2008), in which he reveals the systematic dehumanization and torture in Abu Ghraib Prison by referring to the narratives of the perpetrators. © 2023, Turkish Medical Association. All rights reserved.
Uzbekistan: Political Economy of the Intelligence Services
(Bloomsbury Publishing Plc., 2022) Gormus, E.
Quantifying the Grounding Probability in Narrow Waterways
(CRC Press/Balkema, 2020) Özlem, Ş.; Altan, Y.C.; Otay, E.N.; Or İlhan
The aim of this paper is to estimate the grounding probability of vessels while navigating in narrow waterways. In this study, the grounding probability is modelled as a combination the geometric probability, defined as vessel being on a grounding course and the causation probability, defined as the probability that the vessel is unable to avoid a grounding while being on a grounding course. A mathematical model is developed to estimate the geometric probability where the causation probability is estimated through a specially designed Bayesian network. The Strait of Istanbul, one of the narrowest waterways in the world, is used as a test case. The resulting grounding and ramming accidents are 2.8 times the ship collisions. The most critical causes of grounding accidents are the machine failure, steering inadequacy and lack of pilot support, respectively. With different input parameters, the proposed approach may be applied to other narrow waterways. © 2020 Taylor and Francis Group, London.
Gamifying Cultural Heritage: A Comparative Study of Handheld and Wearable MR Technologies
(Elsevier Ltd, 2026) Gül, L.F.; Özer, D.G.; Yagmur Kilimci, E.S.; Coskun, E.; Moralıoğlu, B.; Yücel, V.
This article presents a comparative, technology-focused analysis with the creation of a game-based route for Yedikule Fortress as its core focus, undertaken as a part of a comprehensive research initiative. We present the development of a narrative-driven, gamified route delivered via two platforms: an Android-based Augmented Reality (AR) tablet application and a Mixed Reality (MR) head-mounted display (HoloLens 2). The route incorporates game elements—such as trivia, treasure hunts, and object completion—within a narrative framework to foster deeper engagement with the site's historical and cultural layers. Employing an experimental mixed-method approach, we iteratively designed, implemented, and refined the experience on both platforms, guided by expert feedback. Special attention was given to aligning game mechanics with the site's spatial and interpretative context, adapting to each platform's affordances for user interaction and narrative delivery. Our findings contribute to the understanding and advancement of spatial computing in creating engaging, educational, and culturally meaningful digital heritage experiences. © 2025 Elsevier Ltd.
Technology in Assessment
(Taylor and Francis, 2025) Birgili, Bengi; Chue, Kah Loong
Language Education and Human Rights in Democratic Educational Settings
(IGI Global, 2025) Rousoulioti, T.; Pitsou, C.; Saglam, A.; Finch, K.
Language education plays a role in human rights within democratic educational settings, where inclusivity and equality are foundational principles. Access to quality language education empowers individuals to participate in society, exercise their rights, and preserve their cultural and linguistic identities. In multilingual and multicultural democracies, ensuring all students can learn languages promotes social cohesion and educational equality. Language education is imperative to human rights, supporting the broader goals of democracy, diversity, and justice in education. Language Education and Human Rights in Democratic Educational Settings explores the critical role of language at all levels of education and its profound impact on the human rights of plurilingual students. By examining the social, pedagogical and legal dimensions of language rights, it highlights how equitable language policies can empower students, foster inclusion, and ensure their right to a democratic education that respects and values their linguistic and cultural identities. This book covers topics such as democracy, artificial intelligence, and language rights, and is a useful resource for educators, sociologists, policymakers, academicians, researchers, and scientists. © 2026 by IGI Global Scientific Publishing. All rights reserved.
Sustainability of Engineered Rivers in Arid Lands: Challenge and Response
(Cambridge University Press, 2021) Schmandt, Jurgen; Kibaroğlu, Ayşegül; Buono, R.M.; Thomas, S.
This interdisciplinary volume examines how nine arid or semi-arid river basins with thriving irrigated agriculture are doing now and how they may change between now and mid-century. The rivers studied are the Colorado, Euphrates-Tigris, Jucar, Limarí, Murray-Darling, Nile, Rio Grande, São Francisco, and Yellow. Engineered dams and distribution networks brought large benefits to farmers and cities, but now the water systems face multiple challenges, above all climate change, reservoir siltation, and decreased water flows. Unchecked, they will see reduced food production and endanger the economic livelihood of basin populations. The authors suggest how to respond to these challenges without loss of food production, drinking water, or environmental health. The analysis of the political, hydrological, and environmental conditions within each basin gives policymakers, engineers, and researchers interested in the water/sustainability nexus a better understanding of engineered rivers in arid lands. © Jurgen Schmandt, Aysegu¨l Kibaroglu, Regina M. Buono and Sephra Thomas 2021.
Gender Differences in Cyber Dating Violence Among Adolescents and Young Adults: A Systematic Review and Meta-Analysis
(Wiley, 2025) Erbicer, Eyup Sabir; Metin, Ahmet; Zencir, Tolga; Boranli, Ece Nur; Demirtas, Ezgi Toplu; Sen, Sedat
Despite the growing body of research on cyber dating violence, a comprehensive understanding of gender differences in cyber-violent behaviors across developmental stages remains limited. The main purpose of this meta-analytic review was to estimate the direction and magnitude of gender differences in cyber dating violence perpetration and victimization by synthesizing results from various studies. The second purpose of this study was to examine the effect of potential moderators (i.e., continent, age, grade level, time frame, method of survey administration, the metric of the outcome, study design, publication status, and publication year) on these differences. Various databases were used to identify relevant studies, including PubMed, Web of Science (WoS), Scopus, PsycINFO, ERIC, and ProQuest. Eighty-one individual studies with a total sample of 70,233 participants, ranging in age from 10 to 30 years (M = 18.94), were included based on the inclusion and exclusion criteria in the present study. Most studies were conducted in North America and Europe with the largest proportions from the United States and Spain. Results indicated that there were no statistically significant gender differences (women vs. men; girls vs. boys) in perpetration and victimization of cyber dating violence. Moderator analyses showed that grade level and sample age were statistically significant moderators of gender differences in cyber dating violence victimization. However, other moderators (continent, time frame, method of survey administration, the metric of the outcome, study design, publication status, and publication year) were not statistically significant. This study contributes to understanding gender differences in cyber-violent behaviors during adolescence and emerging adulthood and highlights the importance of some moderators when developing targeted prevention and intervention strategies.
Powder Metallurgical Synthesis, Thermochemical Calculations and Characterization Studies of HfB2 Powders
(Springer India, 2025) Akbari, Amir; Suzer-Cicek, Ilayda; Mertdinc-Ulkuseven, Siddika; Gokce, Hasan; Ovecoglu, M. Lutfi; Agaogullari, Duygu
This study reports on the thermochemical calculations, mechanochemical synthesis, purification process, and characterization studies of the HfB2 powders by using native sources. Firstly, HfO2, native B2O3, and Mg starting powders were prepared with a multi-axial vibratory ball mill (NanoMultimix) in stoichiometric and excess amounts. The milling process was optimized by varying the time (2, 4, 6, 8, 10, 12 h). Then, unwanted by-products (HfO2, MgO) were removed by leaching with 4 and 6 M HCl. Phase and Rietveld analysis, microstructure investigations with scanning electron microscopy/energy dispersion spectroscopy and transmission electron microscopy, and particle size measurement were conducted. The purest HfB2 was obtained in the powders milled for 8 h in stoichiometric ratios and leached with 6 M HCl. The resulting optimum powder has an average particle size of 135 nm. Oxidation kinetics (500, 600, 700, 800, and 900 degrees C) were also investigated. As the temperature increased, the amount of oxidation increased based on the TG result. As a result of the characterization studies, the synthesis of single-phase, high-purity HfB2 was achieved using domestic resources.
How Does Type of Moral Responsibility Affect the Extent of the Moral Circle? The Influence of Relational Models
(Sage Publications Inc, 2025) Sunar, Diane; Cesur, Sevim; Tepe, Beyza; Piyale, Zeynep Ecem; Hill, Charles T.
The "moral circle" defines entities toward which a person feels moral responsibility. Relational Models Theory (RMT) proposes four basic relational models (communal sharing, authority ranking, equality matching, and market pricing), each with distinct moral motivations. This study applies RMT to define different types of moral responsibility: caring, guiding, obeying/deferring, ensuring equality, or equity. We proposed that the type of moral responsibility may alter a judge's rating of degree of responsibility, affecting the entity's placement within the moral circle. Linear mixed model analyses of responsibility ratings toward various human and other targets across six closeness levels confirmed that relational models significantly affected felt responsibility ratings. Specifically, asking about Equality Matching responsibility (assuring equal rights and treatment) led to higher moral responsibility ratings than other definitions (Communal Sharing, Authority Ranking, Market Pricing), even for negatively judged targets like rapists. The two cultures tested (US and T & uuml;rkiye) differed in average responsibility ratings for various targets, but culture did not interact with Relational Models. Differences in moral inclusiveness are interpreted through relational model characteristics, such as boundedness and rule orientation. In addition to individual, situational, cultural differences, relational models between judge and target also affect extent of the moral circle.
The Role of Artificial Intelligence in Sustainable Food Retailing: A Pathway to Reducing Waste and Enhancing Efficiency
(Springer Science and Business Media B.V., 2026) Köse, Ş.G.; Kazançoǧlu, I.; Kazancoglu, Y.
Food waste arises in the supply chain’s distribution, marketing, and consumption phases. Retailers face problems related to food waste since it increases operating costs, causing savings and loss of profitability. Due to food waste’s environmental, economic, and social impacts, food retailers increasingly incorporating artificial intelligence-based applications into their operations to increase efficiency and ensure sustainability. Demand forecasting, inventory management and optimization, dynamic pricing, supply chain, and order optimization are some of the main artificial intelligence applications utilized to address food waste. In line with this purpose, the paper aims to highlight the importance of artificial intelligence for reducing food waste in retailing. This study focuses on how food retailers increasingly leverage artificial intelligence to reduce food waste and improve sustainability across their operations. This research was conducted through case study and these cases provide applications of artificial intelligence to the food retail industry. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
Evaluating Large Language Models in Data Generation for Low-Resource Scenarios: A Case Study on Question Answering
(International Speech Communication Association, 2025) Arisoy, E.; Menevşe, M.U.; Manav, Y.; Özgür, A.
Large Language Models (LLMs) are powerful tools for generating synthetic data, offering a promising solution to data scarcity in low-resource scenarios. This study evaluates the effectiveness of LLMs in generating question-answer pairs to enhance the performance of question answering (QA) models trained with limited annotated data. While synthetic data generation has been widely explored for text-based QA, its impact on spoken QA remains underexplored. We specifically investigate the role of LLM-generated data in improving spoken QA models, showing performance gains across both text-based and spoken QA tasks. Experimental results on subsets of the SQuAD, Spoken SQuAD, and a Turkish spoken QA dataset demonstrate significant relative F1 score improvements of 7.8%, 7.0%, and 2.7%, respectively, over models trained solely on restricted human-annotated data. Furthermore, our findings highlight the robustness of LLM-generated data in spoken QA settings, even in the presence of noise. © 2025 International Speech Communication Association. All rights reserved.
Turkey's EU Membership Process in the Aftermath of the Gezi Protests
(Taylor and Francis, 2025) Saatçioǧlu, B.
Methane Emissions Forecasting Using Hybrid Quantum-Classical Deep Learning Models: Case Study of North Africa
(Springer, 2025) Belkadi, Widad Hassina; Drias, Yassine; Drias, Habiba; Ferkous, Sarah; Khemissi, Maroua
This study explores climate change by predicting methane emissions in North Africa using classical and quantum deep learning methods. Using data from Sentinel-5P, we developed hybrid quantum-classical models, such as quantum long short-term memory (QLSTM) and quantum-gated recurrent unit networks (QGRUs), along with a novel hybrid architecture combining quantum convolutional neural networks (QCNNs) with LSTM and GRU, namely QCNN-LSTM and QCNN-GRU. The results show that these quantum models, especially the proposed hybrid architectures, outperform classical models by approximately seven percent in root-mean-squared error with fewer training epochs. These findings highlight the potential of quantum methodologies for enhancing environmental monitoring accuracy. Future research will aim to refine model performance, incorporate explainable AI techniques, and expand to forecasting other greenhouse gases, contributing to climate change mitigation efforts.
Big-5 Personality Traits as Predictors of Allostatic Load in Latino Americans: A Longitudinal Study
(Oxford Univ Press Inc, 2025) Sevi, Baris; Supiyev, Adil; Gutierrez, Angela; Graham, Eileen K.; Mroczek, Daniel K.; Muniz-Terrera, Graciela
Objectives Allostatic load (AL) refers to the measure of cumulative wear and tear resulting from chronic stress and life events. AL presents adverse consequences for a diverse range of health conditions, and Latino populations show a high risk for elevated AL. This study aimed to test the Big-5 personality traits as possible predictors of AL in Latinos.Methods Using data from the Health and Retirement Study, we examined the Big-5 and AL connection through three time points in 8 years (Time 1 = 2006/2008; Time 2 = 2010/2012; Time 3 = 2014/2016). Only self-identified Latinos were included in the analysis sample (N = 319). Big-5 and demographics were obtained at baseline, and AL scores were computed for each time point.Results First, separate longitudinal linear mixed-effect models examined the effects of each Big-5 personality trait on AL change over time, then a fully adjusted longitudinal linear mixed-effect model was tested entering the Big-5 personality traits simultaneously. All models controlled for sociodemographic factors. Conscientiousness emerged as the only consistent significant predictor, for the separate and the simultaneous models. In baseline associations, higher conscientiousness was associated with lower AL. For predicting change in AL over time, none of the personality traits had significant associations in any of the models.Discussion The findings bolster prior evidence that conscientious can be a protective factor against elevated AL. Conscientiousness is a possible protective factor and improving related traits can be a path to achieve better health in Latino Americans.
Moral Framing Effects on Environmental Attitudes: A Conceptual Replication and Extension of Feinberg and Willer (2013)
(Academic Press Ltd- Elsevier Science Ltd, 2025) Cavdar, Dilara; Tepe, Beyza; Saribay, S. Adil; Yilmaz, Onurcan
This study investigates the relationship between moral framing, political orientation, and pro-environmental attitudes, replicating and extending Feinberg and Willer (2013) in a non-Western context. Using a Turkish-speaking sample (N = 699), we examined the effectiveness of care and sanctity-framed messages and the moderating role of actively open-minded thinking (AOT). Our findings partially replicated the original study. Sanctity framing increased pro-environmental attitudes among conservatives, while care framing had no significant effect. Political conservatism was negatively associated with pro-environmental attitudes, confirming prior findings. Exploratory analyses revealed that AOT moderated the effects of sanctity framing on environmental attitudes, with individuals low or moderate in AOT being more responsive. Both care and sanctity frames increased environmental donation, addressing the intention-behavior gap. However, cultural nuances, such as the collectivist orientation of the sample, may have influenced the care frame's ineffectiveness. The study highlights the importance of cultural context in moral framing research and underscores the need for context-specific climate communication strategies.
Testing Soft Power in Hard Politics: Turkish Public Diplomacy During “Operation Peace Spring”
(Palgrave Macmillan, 2025) Güleç Aras, Cansu; Kibaroğlu, Mustafa
Public diplomacy is used by governments to significantly enhance their capability to maintain national unity and integrity as well as to advance their foreign policy objectives by cultivating a favorable environment among foreign peoples. In conflictual situations where military force is used, it is important to create an impact in a short time to promote national interests by informing and influencing the public. This chapter will first introduce the fundamental tenets of public diplomacy to offer a conceptual framework to better understand its use during military conflicts. It will then explore the implementation of public diplomacy instruments by Turkish government during the “Operation Peace Spring”, which was launched in October 2019. The chapter will also assess the performance of Turkish public diplomacy in the face of the extent of criticism leveled against Türkiye from around the world, including allied countries and international organizations.
Enhanced Knowledge Transfer in Historical Site Interpretation: A Gamified Approach for Yedikule Fortress/Türkiye
(Springer Science and Business Media Deutschland GmbH, 2025) Özer, D.G.; Gül, L.F.; Coskun, E.; Kilimci, E.S.Y.; Gül, M.
This study explores the integration of wearable and portable devices in enhancing the interpretation and communication of Yedikule Fortress, a 1600-year-old historical site on the outskirts of the Istanbul’s Historic Peninsula. This interpretation involves users taking of the site tour with augmented reality/mixed reality-enhanced using audio accompaniment and gamification. The designed route provides tailored information, enhanced by a digital layer and a storyline. This study examines the quality of the information, visitor route design, and the integration of game elements. The multi-modal guidance system fosters interaction between historical narratives and spatial context, with participants reporting increased interest and improved recall of historical details. Building on the refinement of the process through expert input and participant feedback, this study also highlights limitations related to device affordances that influenced user behavior and interaction. Future research should explore the adaptability of this framework to other heritage sites, ensuring its educational and experiential relevance. © 2025 Elsevier B.V., All rights reserved.
Quantum FP-Growth Algorithm Using GPU Simulation-Application to Digital Soil Mapping
(Elsevier, 2026) Belkadi, Widad Hassina; Drias, Yassine; Drias, Habiba
This study introduces a novel quantum version of the FP-growth algorithm for frequent itemset mining, leveraging the combined strengths of classical FP-growth and quantum machine learning. Key contributions include the theoretical and practical framework for Quantum FP-growth, along with a comprehensive analysis of its time and space complexity. We implemented Quantum FP-growth using IBM Qiskit and conducted a comparative evaluation of various quantum amplitude estimation (QAE) methods, including Canonical QAE, Faster QAE, Maximum Likelihood QAE, and Iterative QAE for support estimation. Our findings reveal that Iterative QAE surpasses the other methods in both accuracy and speed. Additionally, we explored the advantages of GPU simulation with IBM Qiskit and NVIDIA cuQuantum. Notably, this research marks the first application of a quantum frequent itemset mining algorithm to a real-world dataset in Digital Soil Mapping (DSM), pioneering the use of quantum technologies in soil science. This study underscores the potential of quantum computing to revolutionize data mining and promote sustainable soil management practices.

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