WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Widening the Moral Circle: Perceived Responsibility and Guilt as Mediators of Moral Expansiveness and pro-Environmental Behavior(Springer, 2026) Sari, Erkin; Coskun, Muhammet; Cingoz-ulu, Banu; Candanoglu, InciPrevious research has shown that moral constructs, such as personal norms, play a significant role in shaping individuals' pro-environmental engagement. However, the specific influence of moral expansiveness on such behaviors has received limited attention in the existing literature. This study aims to investigate the relationship between moral expansiveness and pro-environmental engagement within the Turkish context, which is particularly vulnerable to the impacts of climate change. It specifically examines the mediating roles of perceived environmental responsibility and environmental guilt to better understand the mechanisms underlying this association. In total, 244 undergraduate students (167 women, 76 men, 1 did not state; Mage = 21.95, SDage = 2.58) participated in the current study in exchange for course credit. Findings indicated that moral expansiveness indirectly predicted pro-environmental behaviors through both perceived environmental responsibility and environmental guilt, although its direct effect was not significant. Perceived environmental responsibility and environmental guilt both significantly predicted pro-environmental behaviors. Additionally, individuals with more left-leaning political views reported higher levels of pro-environmental behavior. This study highlights how broader moral concern can support sustainability, while contributing to the inclusion of non-Western contexts in environmental psychology.Article Surface Integrity and Tool Wear in S2-GFRP Milling: Experimental and Statistical Evaluation of Cutting Parameters and DLC and TiAlN Tool Coatings(Springer London Ltd, 2026) Danisman, Sengul; Yilmaz, Cagatay; Ersoy, Emin; Kesriklioglu, SinanIn this study, the surface integrity of S2-glass fiber-reinforced polymer (S2-GFRP) composites during milling with carbide cutters was investigated using a two-phase experimental design, focusing on surface roughness (Ra), burr area, and tool wear (VB). In the first phase, using a Taguchi L9 design, the effects of coating type (uncoated, TiAlN, DLC), spindle speed (2000-6000 rpm), and feed rate (0,15-0,25 mm/rev) on Ra and burr area were evaluated. In this short machining range where tool wear was negligible, the optimal combination yielding the lowest Ra (approximate to 0.97 mu m) and the minimum burr area (approximate to 231 mm & sup2;) was determined to be 4000 rpm, 0,15 mm/rev, and the DLC-coated tool. Regarding the effect of tool material on Ra, the DLC-coated tool provided approximately 4 and 2 times better results than the uncoated and TiAlN-coated tools, respectively. In the second phase, experiments extended up to 130 passes with this optimal parameter set showed that Ra increased significantly with increasing VB, and the burr area exhibited threshold-like behavior. In particular, a sudden increase in Ra and the burr area was observed when the VB approximate to threshold of approximately 100 mu m was exceeded; partial regression analyses confirmed different burr-formation tendencies in the low- and high-wear regimes. The results reveal that DLC coating initially provides superior performance in S2-GFRP milling, but surface degradation accelerates after the critical VB threshold.Article Structural Optimization for Robotic Concrete Construction: A Systematic Review(MDPI, 2026) Gürer, Ethem; Pektaş, Ömer Korkut; Alaçam, Sema; Güzelci, Orkan Zeynel; Çevik, Ayşe Nesligül; Türel, Ahmet; Özdemir, SalihConcrete construction is associated with high environmental impact and geometric limitations imposed by conventional formwork, which has led to growing interest in combining structural optimization with robotic fabrication. In this study, structural optimization refers to computational methods such as topology optimization, shape optimization, and form finding that aim to improve material efficiency and load-bearing performance by modifying the geometry of structural elements. This systematic review investigates how these optimization approaches are translated into fabrication-aware design workflows for robotic concrete construction. Following a PRISMA-based methodology, 90 peer-reviewed studies published between 2015 and 2025 were analyzed. The review focuses on fabrication routes including (i) 3D concrete printing, (ii) 3D-printed formwork, (iii) shotcrete-based additive manufacturing, and (iv) controlled casting systems, and examines how each route constrains geometry representation, design decisions, toolpath generation, and robotic execution. The review analyzes design-to-fabrication workflows that link optimized structural geometry to production logic and process control. Key findings indicate that incorporating fabrication constraints at early design stages can support buildability and potential material efficiency, while reinforcement integration and quality control remain critical challenges for structural reliability. The review also highlights the increasing role of in situ sensing and feedback-driven automation in improving process stability. Overall, the study clarifies current practices, limitations, and emerging directions for integrating structural optimization with robotic concrete fabrication.Article From Agility to Advocacy: Exploring How Gender Moderates the Impact of Social Media Agility on Brand Trust and Influencing Behavior(Palgrave Macmillan Ltd, 2026) Bozkurt, Sıddık; Gligor, David; Hollebeek, Linda D.; Sarp, SerapThis research investigates the effect of perceived social media agility (P-SMA) on customers' influencing behavior, a theoretical subset of engagement behavior, with brand trust acting as a mediator and gender (male/female) as a moderator. It also explores how these relationships differ across age groups. Two online surveys were conducted: Study 1 with 165 younger participants and Study 2 with 178 adults. Using PROCESS Macro Models 4 and 7, we tested direct, mediated, and moderated mediation effects. Both studies found that P-SMA enhances brand trust, which subsequently mediates its influence on customer behavior. Study 2 confirmed these results, showing that gender moderates the relationship between P-SMA and both brand trust and influencing behavior, with stronger effects observed among females (vs. males) in both samples. The findings highlight the importance of tailoring social media strategies to gender-based engagement patterns. Crafting content and interaction styles that foster trust can improve influence and advocacy, especially when agility is a key element of the brand's digital presence. This research integrates P-SMA, brand trust, and customer influence behavior within a moderated mediation model. Using two age-diverse samples, it shows gender shapes reactions to brand agility, while age differences remain non-significant across both datasets.Article Driving Sustainability and Sustainable Developmental Goals in Hospitality: The Influence of Green HRM, Environmental CSR and Shared Green Vision on Pro-Environmental Behaviour(Wiley, 2026) Rafiq, Nosheen; Bulbul, Yagiz Efe; Cobanoglu, Cihan; Shah, Syed Haider Ali; Raza, GulzaibEnvironmental sustainability is highly dependent on the employees' pro-environmental behaviour (PEB) particularly in the hospitality industry context, yet there is still a gap of explanation on mechanisms that systematically improve employees' PEB. Based on Social Identity Theory, this study attempts to examine how green human resource management (GHRM) practices influence employees' PEB in two paths, directly and indirectly, through dual mediating mechanisms: environmental corporate social responsibility (ECSR) and green shared vision (GSV). Using a quantitative design, the study data were collected from 449 hotel managers through a structured questionnaire and analyzed with SmartPLS (SEM). The results show that GHRM has a significant positive effect on PEB and also through indirect effects of both ECSR and GSV. Further, the model explains the substantial amount of variance in PEB. The effect size reveals that indirect pathways are stronger mechanisms than the direct path from GHRM to PEB. Through bringing together the collective cognitive and identity based aspects into one framework, this study extends the theoretical understanding of mechanisms of how GHRM transform sustainability strategies into employee level environmental engagement, which is also aligned with the Sustainable Development Goals (SDGs). The study empirically broadens the GHRM research in the hospitality sector within developing country context and also presents multiple practical insights for hotel policymakers and managers to synchronize environmental strategies with employee conduct.Article Time Distributed Classification of Alzheimer’s Disease on MRI Scans(John Wiley and Sons Ltd, 2026) Dundar, Mehmet Sait; Yilmaz, BulentThe diagnosis of Alzheimer's disease (AD) has progressively depended on sophisticated neuroimaging methods alongside cognitive assessments. This study combines volumetric feature analysis with computational modeling techniques, focusing on spatial and temporal analysis, to categorize individuals as cognitively normal (CN), mild cognitive impairment (MCI), or AD using magnetic resonance imaging (MRI) data. In the initial phase, volumetric changes, comprising cortical thickness, white matter, grey matter, cerebrospinal fluid, and total intracranial volume, were derived from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset utilizing the CAT12 toolbox in statistical parametric mapping (SPM). Linear regression was utilized on these variables over time to create slopes that reflect volumetric change rates, which then served as inputs for machine learning classifiers. The slopes of cortical thickness exhibited the greatest classification accuracy, reaching 82.5% with a random forest model for differentiating AD from CN individuals. During the second phase, a deep learning methodology was utilized, relying solely on the MRI scans and excluding the outcomes from the first phase. A pre-trained 3D ResNet-101 convolutional neural network (CNN) model extracted spatial characteristics from MRI volumes, whereas long short-term memory (LSTM) networks recorded temporal dynamics across subsequent annual scans. This hybrid CNN-LSTM design markedly improved classification performance, attaining 96.7% accuracy for AD against CN and enhancing the distinction of MCI cases. Nonetheless, discrepancies in MCI categorization were chiefly ascribed to the restricted access to annual MRI data and the model's pre-training on CN and AD cohorts. These findings highlight the potential of integrating volumetric statistical analysis with deep learning for automated AD categorization. This work enhances neuroimaging diagnostic methods by utilizing both spatial and temporal MRI data, enabling early diagnosis and better evaluation of disease development.Article Threat Landscape of Edge-AI-Assisted Connected Autonomous Vehicles (CAV)(Elsevier B.V., 2026) He, Ligang; Maple, Carsten; Atmaca, Ugur Ilker; Kasyap, Harsh; Nezhad, Mahshid Mehr; Atmacaa, Ugur Ilker; Nezhada, Mahshid Mehr; Kasyapa, HarshConnected Autonomous Vehicles (CAVs) powered by Edge Artificial Intelligence (Edge-AI) are revolutionising intelligent transportation systems through real-time data processing for obstacle avoidance, adaptive learning of dynamic traffic patterns, and improved decision-making in safety-critical tasks like traffic sign recognition. However, deploying machine learning (ML) models directly at the vehicle level introduces new security vulnerabilities, making CAVs susceptible to adversarial attacks that can compromise system integrity, reliability, and safety. These attacks primarily target onboard ML systems, highlighting the need for a structured threat modelling approach to identify and mitigate risks. This paper investigates the threat landscape of Edge-AI-assisted CAVs, focusing on the CAV layer as a critical attack surface within the hierarchical system architecture. Employing the STRIDE framework, we analyse vulnerabilities across four stages of the ML lifecycle: input data, model training, aggregation and inference. We present adversarial concept drift as a case study of an evolving threat in which malicious actors introduce subtle data manipulations over time to degrade ML model performance while avoiding detection. Through attack tree analysis and experimental evaluation, we show how adversarial concept drift propagates through the system, ultimately affecting its reliability. To the best of our knowledge, this is the first study to illustrate the impact of gradual adversarial concept drift on robustness. Our results reveal that gradual drifts are harder to detect than sudden ones, even when using Byzantine-robust defenses. These findings underscore the limitations of existing security mechanisms and emphasise the urgent need for adaptive, resilient countermeasures to address the dynamic, evolving threat landscape facing Edge-AI-enabled CAV systems.Article SDG-Oriented Compulsory Courses in Higher Education: An Exploratory Case from Turkey(Emerald Group Publishing Ltd, 2026) Gover, Ibrahim Hakan; Ayten, Asim MustafaPurpose This study aims to examine students' perceptions of a set of compulsory Sustainable Development Goal (SDG)-oriented courses implemented across undergraduate programmes at a newly-established Turkish state university. Rather than evaluating individual courses, the study explores how a compulsory, SDG-framed curricular approach is associated with students' reported sustainability awareness, civic orientation and social engagement within a specific institutional context.Design/methodology/approach Data were collected from 325 undergraduate students enrolled in four compulsory SDG-oriented courses during the 2024-2025 academic year using a non-probability convenience sampling approach. A 19-item structured survey was administered to capture students' self-reported awareness and attitudes related to sustainability and social responsibility. Descriptive and inferential analyses (including t-tests and ANOVA after verifying normality assumptions) were conducted using SPSS and R.Findings The findings, derived from a composite impact scale, suggest that participation in SDG-oriented compulsory courses is associated with higher levels of sustainability awareness and positive orientations towards civic responsibility and social engagement. Differences were observed across demographic groups, with female students and those reporting prior familiarity with sustainability concepts indicating stronger perceived impacts. Given the exploratory design and reliance on self-reported data, the results should be interpreted as indicative rather than conclusive.Research limitations/implications The study is limited by its cross-sectional design, convenience sampling and reliance on self-reported perceptual data, which restricts causal interpretation and generalisability. The findings capture the initial, formative stages of learning rather than long-term transformation. As the data were collected from students enrolled in the earlier and intermediate stages of a set of compulsory SDG-based courses, the findings do not capture longer-term educational effects associated with the full curricular sequence. Future research employing longitudinal and comparative designs could provide deeper insight into how SDG-oriented curricular approaches develop over time and across institutional contexts.Practical implications The study provides empirical insight into how compulsory, SDG-oriented courses may contribute to students' sustainability-related awareness and civic orientations within higher education curricula. For curriculum developers and policymakers, the findings highlight both the potential and the limitations of using dedicated courses as one possible approach to embedding education for sustainable development.Social implications By foregrounding students' perspectives, the study contributes to ongoing discussions on the role of higher education in supporting sustainability-oriented values and social responsibility.Originality/value This study contributes exploratory, context-specific evidence on students' perceptions of SDG-oriented compulsory courses in Turkish higher education, offering a cautious empirical basis for further discussion and research on education for sustainable development at the institutional level.Article Radar Resolution Enhancement Based on Burg-Aided MIMO-DBS and Burg-Aided MIMO-SAR †(MDPI, 2026) Bekar, Muge; Bekar, Ali; Baker, Christopher John; Gashinova, Marina; Pirkani, AnumAutonomous systems require sensors that provide high-resolution imagery in adverse lighting and weather conditions for advanced situational awareness. In this regard, radars are a mandatory component of autonomous systems. Although Multiple-Input Multiple-Output (MIMO) radars provide high angular resolution beyond that of their actual physical dimension, much higher cross-range resolutions are required, especially in traffic congested areas, to differentiate and recognize closely positioned targets. The motion of the MIMO radar platform can be exploited to obtain higher cross-range resolution in the off-boresight direction, using Synthetic Aperture Radar (SAR) and Doppler Beam Sharpening (DBS) techniques, but improvements in the boresight direction, the most crucial direction for path planning, require the use of super-resolution techniques. This paper proposes a technique that combines the Burg algorithm with MIMO-SAR and MIMO-DBS radar data to enhance the cross-range resolution in the boresight direction and to achieve further enhanced cross-range resolution in off-boresight directions. The proposed technique is applied to both frequency domain and time domain data in back-projection (BP) and DBS image formation processing. A comprehensive comparison is made, with evaluation of corresponding performance and operational complexity. The performance of the technique is validated through simulation, lab-based and real-world experiments at a frequency of 77 GHz.Article Institutions and Bank Intermediation: The Joint Role of State Capacity and Civil Liberties(Wiley, 2026) Raz, Arisyi F.; Gokmen, SeyitWe examine the effects of state capacity and civil liberties on bank intermediation, measured by banks' ability to generate liquidity in the economy. Theory suggests that a strong state that upholds civil liberties can create institutions that promote economic activity, including the development of its banking sector. We investigate this hypothesis by testing a possible channel: confidence in the banking system. Democracies tend to increase trust in the banking system by reforming institutions, while autocracies frequently rely on cronyism. Over the long run, trust in the banking system promotes banking development and intermediation in democracies, whereas cronyism and the risk of expropriation by autocrats undermine the potential for banking sector advancement in autocracies, despite having a trustworthy banking system. Our findings provide evidence in support of this channel, offering new insights into the role of political institutions in the banking sector.